From 23692e590a55332635c43dc7c90e7bf2cd8e6769 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 8 Sep 2021 09:46:37 +0200 Subject: [PATCH 001/218] projectors in factor graph are 1-dimensional --- src/factor.jl | 29 +++++++++++++++++++++++++++-- test/factor.jl | 32 ++++++++++++++++++++++++++------ 2 files changed, 53 insertions(+), 8 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 26a521c..55c367a 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -1,4 +1,4 @@ -export factor_graph, rank_reveal, projectors, split_into_clusters, decode_factor_graph_state +export factor_graph, rank_reveal, projectors, split_into_clusters, decode_factor_graph_state, proj function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} @@ -72,7 +72,7 @@ function factor_graph( ) where {T} factor_graph(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end - +#= function rank_reveal(energy, order=:PE) @assert order ∈ (:PE, :EP) dim = order == :PE ? 1 : 2 @@ -89,10 +89,35 @@ function rank_reveal(energy, order=:PE) elements[idx[i]] = 1 end + order == :PE ? (P, E) : (E, P) +end=# + +function rank_reveal(energy, order=:PE) + @assert order ∈ (:PE, :EP) + dim = order == :PE ? 1 : 2 + E, idx = unique_dims(energy, dim) + P = identity.(idx) + order == :PE ? (P, E) : (E, P) end +function proj(idx, order=:PE) + @assert order ∈ (:PE, :EP) + dim = order == :PE ? 1 : 2 + if order == :PE + P = zeros(size(idx, 1), maximum(idx)) + else + P = zeros(maximum(idx), size(idx, 1)) + end + + for (i, elements) ∈ enumerate(eachslice(P, dims=dim)) + elements[idx[i]] = 1 + end + P +end + + function decode_factor_graph_state(fg, state::Vector{Int}) ret = Dict{Int, Int}() for (i, vert) ∈ zip(state, vertices(fg)) diff --git a/test/factor.jl b/test/factor.jl index 1f0689d..dd8d8c4 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -114,7 +114,15 @@ end energy[ii, jj] = eij end end - @test energy ≈ pl * (en * pr) + println("pl", pl) + println("proj(pl) ", proj(pl, :PE)) + println("en", en) + println("pr", pr) + println("proj(pr) ", proj(pr, :EP)) + + #@test energy ≈ pl * (en * pr) + @test energy ≈ proj(pl, :PE) * (en * proj(pr, :EP)) + println("-----------") end @testset "each cluster comprises expected cells" begin @@ -137,7 +145,11 @@ end @testset "Rank reveal correctly decomposes energy row-wise" begin energy = [[1 2 3]; [0 -1 0]; [1 2 3]] - P, E = rank_reveal(energy, :PE) + PP, E = rank_reveal(energy, :PE) + P = proj(PP, :PE) + println("P ", P) + println("E ", E) + @test length(PP) == 3 @test size(P) == (3, 2) @test size(E) == (2, 3) @test P * E ≈ energy @@ -145,7 +157,11 @@ end @testset "Rank reveal correctly decomposes energy column-wise" begin energy = [[1, 2, 3] [0, -1, 1] [1, 2, 3]] - E, P = rank_reveal(energy, :EP) + E, PP = rank_reveal(energy, :EP) + P = proj(PP, :EP) + println("E ", E) + println("P ", P) + @test length(PP) == 3 @test size(P) == (2, 3) @test size(E) == (3, 2) @test E * P ≈ energy @@ -163,12 +179,16 @@ end [0.0 -0.5 -0.5 -1.0 1.0 0.5 0.5 0.0]; [-1.0 0.5 -1.5 0.0 0.0 1.5 -0.5 1.0] ] - Pl, E_old = rank_reveal(energy, :PE) + PPl, E_old = rank_reveal(energy, :PE) + Pl = proj(PPl, :PE) + @test length(PPl) == 8 @test size(Pl) == (8, 8) @test size(E_old) == (8, 8) @test Pl * E_old ≈ energy - E, Pr = rank_reveal(E_old, :EP) + E, PPr = rank_reveal(E_old, :EP) + Pr = proj(PPr, :EP) + @test length(PPr) == 8 @test size(Pr) == (8, 8) @test size(E) == (8, 8) @test E * Pr ≈ E_old @@ -280,7 +300,7 @@ function factor_graph_energy(fg, state) for edge ∈ edges(fg) i, j = fg.reverse_label_map[src(edge)], fg.reverse_label_map[dst(edge)] pl, en, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :en), get_prop(fg, edge, :pr) - edge_energy = pl * en * pr + edge_energy = proj(pl, :PE) * en * proj(pr, :EP) total_en += edge_energy[state[i], state[j]] end From 551e0d1002c6114e6fec2cc85bb6785490437065 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 9 Sep 2021 08:19:46 +0200 Subject: [PATCH 002/218] clean up --- src/factor.jl | 5 +++-- test/factor.jl | 22 ++++++---------------- 2 files changed, 9 insertions(+), 18 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 55c367a..e75c0e7 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -1,4 +1,4 @@ -export factor_graph, rank_reveal, projectors, split_into_clusters, decode_factor_graph_state, proj +export factor_graph, rank_reveal, projectors, split_into_clusters, decode_factor_graph_state, decode_projector function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} @@ -72,6 +72,7 @@ function factor_graph( ) where {T} factor_graph(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end + #= function rank_reveal(energy, order=:PE) @assert order ∈ (:PE, :EP) @@ -102,7 +103,7 @@ function rank_reveal(energy, order=:PE) end -function proj(idx, order=:PE) +function decode_projector(idx, order=:PE) @assert order ∈ (:PE, :EP) dim = order == :PE ? 1 : 2 if order == :PE diff --git a/test/factor.jl b/test/factor.jl index dd8d8c4..6493d11 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -114,15 +114,9 @@ end energy[ii, jj] = eij end end - println("pl", pl) - println("proj(pl) ", proj(pl, :PE)) - println("en", en) - println("pr", pr) - println("proj(pr) ", proj(pr, :EP)) #@test energy ≈ pl * (en * pr) - @test energy ≈ proj(pl, :PE) * (en * proj(pr, :EP)) - println("-----------") + @test energy ≈ decode_projector(pl, :PE) * (en * decode_projector(pr, :EP)) end @testset "each cluster comprises expected cells" begin @@ -146,9 +140,7 @@ end @testset "Rank reveal correctly decomposes energy row-wise" begin energy = [[1 2 3]; [0 -1 0]; [1 2 3]] PP, E = rank_reveal(energy, :PE) - P = proj(PP, :PE) - println("P ", P) - println("E ", E) + P = decode_projector(PP, :PE) @test length(PP) == 3 @test size(P) == (3, 2) @test size(E) == (2, 3) @@ -158,9 +150,7 @@ end @testset "Rank reveal correctly decomposes energy column-wise" begin energy = [[1, 2, 3] [0, -1, 1] [1, 2, 3]] E, PP = rank_reveal(energy, :EP) - P = proj(PP, :EP) - println("E ", E) - println("P ", P) + P = decode_projector(PP, :EP) @test length(PP) == 3 @test size(P) == (2, 3) @test size(E) == (3, 2) @@ -180,14 +170,14 @@ end [-1.0 0.5 -1.5 0.0 0.0 1.5 -0.5 1.0] ] PPl, E_old = rank_reveal(energy, :PE) - Pl = proj(PPl, :PE) + Pl = decode_projector(PPl, :PE) @test length(PPl) == 8 @test size(Pl) == (8, 8) @test size(E_old) == (8, 8) @test Pl * E_old ≈ energy E, PPr = rank_reveal(E_old, :EP) - Pr = proj(PPr, :EP) + Pr = decode_projector(PPr, :EP) @test length(PPr) == 8 @test size(Pr) == (8, 8) @test size(E) == (8, 8) @@ -300,7 +290,7 @@ function factor_graph_energy(fg, state) for edge ∈ edges(fg) i, j = fg.reverse_label_map[src(edge)], fg.reverse_label_map[dst(edge)] pl, en, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :en), get_prop(fg, edge, :pr) - edge_energy = proj(pl, :PE) * en * proj(pr, :EP) + edge_energy = decode_projector(pl, :PE) * en * decode_projector(pr, :EP) total_en += edge_energy[state[i], state[j]] end From 772595fae23c3839bd731bb37ac8636bc74ab6b1 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Mon, 18 Oct 2021 16:23:27 +0200 Subject: [PATCH 003/218] new way of loading J and states --- src/factor.jl | 38 ++++++++ test/instances/pathological/cross_3_4_dd.txt | 95 ++++++++++++++++++++ test/new_factor.jl | 22 +++++ test/runtests.jl | 5 +- 4 files changed, 159 insertions(+), 1 deletion(-) create mode 100644 test/instances/pathological/cross_3_4_dd.txt create mode 100644 test/new_factor.jl diff --git a/src/factor.jl b/src/factor.jl index e75c0e7..1d0fbb8 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -31,6 +31,7 @@ function factor_graph( ) end + function factor_graph( ig::IsingGraph, num_states_cl::Dict{T, Int}; @@ -46,16 +47,52 @@ function factor_graph( end for (i, v) ∈ enumerate(vertices(fg)), w ∈ vertices(fg)[i+1:end] + cl1, cl2 = get_prop(fg, v, :cluster), get_prop(fg, w, :cluster) outer_edges, J = inter_cluster_edges(ig, cl1, cl2) if !isempty(outer_edges) + ind1 = any(i -> i != 0, J, dims=2) + ind2 = any(i -> i != 0, J, dims=1) + ind1 = reshape(ind1, length(ind1)) + ind2 = reshape(ind2, length(ind2)) + JJ = J[ind1, ind2] + # println("J = ", J) + # println("JJ = ", JJ) + states_v = get_prop(fg, v, :spectrum).states + states_w = get_prop(fg, w, :spectrum).states + reduced_states_v = [s[ind1] for s in states_v] + reduced_states_w = [s[ind2] for s in states_w] + + println("rv = ", reduced_states_v) + println("rw = ", reduced_states_w) + + pl, unique_states_v = rank_reveal(reduced_states_v, :PE) + pr, unique_states_w = rank_reveal(reduced_states_w, :PE) + println("uv = ", unique_states_v, pl) + println("uw = ", unique_states_w, pr) + + # println("statesv ", statesv) + # println("statesw ", statesw) + + eng = inter_cluster_energy( + unique_states_v, JJ, unique_states_w + ) + println("en ", eng) + + println("states v ", get_prop(fg, v, :spectrum).states) + println("states w ", get_prop(fg, w, :spectrum).states) + en = inter_cluster_energy( get_prop(fg, v, :spectrum).states, J, get_prop(fg, w, :spectrum).states ) + #println("energy ", en) + #println("----------------") pl, en = rank_reveal(en, :PE) en, pr = rank_reveal(en, :EP) + println("energy_rank_reveal ", en) + println("----------------") add_edge!(fg, v, w) set_props!( fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) @@ -65,6 +102,7 @@ function factor_graph( fg end + function factor_graph( ig::IsingGraph; spectrum::Function=full_spectrum, diff --git a/test/instances/pathological/cross_3_4_dd.txt b/test/instances/pathological/cross_3_4_dd.txt new file mode 100644 index 0000000..914e665 --- /dev/null +++ b/test/instances/pathological/cross_3_4_dd.txt @@ -0,0 +1,95 @@ +# i j Jij +1 2 0.034238 +1 3 0.750061 +1 4 0.589578 +2 3 0.429516 +2 17 0.189869 +3 14 -0.928508 +4 5 -0.870021 +4 14 -0.397741 +5 6 0.951815 +5 9 -0.443220 +5 15 -0.157941 +6 8 0.590863 +6 9 -0.251337 +6 16 0.574823 +7 16 0.080566 +7 24 0.865862 +8 11 0.822161 +9 12 -0.641085 +9 19 -0.984943 +11 12 0.114662 +11 21 0.921200 +12 22 -0.380927 +13 14 0.144119 +13 17 -0.277623 +14 15 -0.190409 +14 16 0.254528 +14 28 -0.248506 +15 18 0.278264 +15 26 0.533558 +15 30 -0.687650 +16 17 -0.188157 +16 18 -0.622391 +16 19 0.866969 +16 20 0.684857 +16 21 -0.643313 +17 18 0.240160 +17 19 -0.891268 +17 20 0.737441 +17 21 -0.493823 +17 32 -0.399723 +18 19 -0.293740 +18 20 -0.830321 +18 21 -0.900943 +18 26 -0.360702 +18 30 0.970748 +19 22 0.938969 +21 31 -0.075877 +22 23 -0.358612 +22 24 0.400141 +22 33 -0.383378 +23 31 0.144978 +23 24 -0.536495 +24 32 0.382778 +26 28 0.943578 +26 30 0.439463 +28 33 -0.846265 +30 31 -0.217551 +31 33 -0.734566 +1 1 0.200000 +2 2 0.146667 +3 3 -0.173333 +4 4 -0.200000 +5 5 0.013333 +6 6 0.040000 +7 7 0.013333 +8 8 0.120000 +9 9 -0.093333 +11 11 0.120000 +12 12 0.173333 +13 13 0.093333 +14 14 0.040000 +15 15 -0.146667 +16 16 -0.146667 +17 17 -0.146667 +18 18 -0.013333 +19 19 0.173333 +20 20 -0.066667 +21 21 0.066667 +22 22 -0.120000 +23 23 -0.173333 +24 24 0.120000 +26 26 -0.093333 +28 28 -0.173333 +30 30 -0.146667 +31 31 0.120000 +32 32 -0.120000 +33 33 -0.200000 +#34 34 0.0 +#35 35 0.0 +#36 36 0.0 +#25 25 0.0 +#27 27 0.0 +#10 10 0.0 +#29 29 0.0 \ No newline at end of file diff --git a/test/new_factor.jl b/test/new_factor.jl new file mode 100644 index 0000000..4255071 --- /dev/null +++ b/test/new_factor.jl @@ -0,0 +1,22 @@ +@testset "Factor graph builds on pathological instance" begin + m = 3 + n = 4 + t = 3 + + β = 1. + + schedule = 1. + + L = n * m * t + states_to_keep = 20 + + instance = "$(@__DIR__)/instances/pathological/cross_$(m)_$(n)_dd.txt" + ig = ising_graph(instance) + + fg = factor_graph( + ig, + spectrum=full_spectrum, + cluster_assignment_rule=super_square_lattice((m, n, t)) + ) + +end \ No newline at end of file diff --git a/test/runtests.jl b/test/runtests.jl index bd783a3..8b42a4d 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -7,7 +7,10 @@ using Test Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) -my_tests = ["ising.jl", "factor.jl"] +my_tests = [ + #"ising.jl", "factor.jl", + "new_factor.jl" + ] for my_test ∈ my_tests include(my_test) From 85ddaccef1d094c45925da7ed55aac1d13ab277c Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Mon, 18 Oct 2021 16:35:28 +0200 Subject: [PATCH 004/218] clean up --- src/factor.jl | 45 ++------------------------------------------- test/runtests.jl | 5 +---- 2 files changed, 3 insertions(+), 47 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 1d0fbb8..1835ffd 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -58,41 +58,19 @@ function factor_graph( ind1 = reshape(ind1, length(ind1)) ind2 = reshape(ind2, length(ind2)) JJ = J[ind1, ind2] - # println("J = ", J) - # println("JJ = ", JJ) + states_v = get_prop(fg, v, :spectrum).states states_w = get_prop(fg, w, :spectrum).states reduced_states_v = [s[ind1] for s in states_v] reduced_states_w = [s[ind2] for s in states_w] - println("rv = ", reduced_states_v) - println("rw = ", reduced_states_w) - pl, unique_states_v = rank_reveal(reduced_states_v, :PE) pr, unique_states_w = rank_reveal(reduced_states_w, :PE) - println("uv = ", unique_states_v, pl) - println("uw = ", unique_states_w, pr) - - # println("statesv ", statesv) - # println("statesw ", statesw) - eng = inter_cluster_energy( + en = inter_cluster_energy( unique_states_v, JJ, unique_states_w ) - println("en ", eng) - - println("states v ", get_prop(fg, v, :spectrum).states) - println("states w ", get_prop(fg, w, :spectrum).states) - en = inter_cluster_energy( - get_prop(fg, v, :spectrum).states, J, get_prop(fg, w, :spectrum).states - ) - #println("energy ", en) - #println("----------------") - pl, en = rank_reveal(en, :PE) - en, pr = rank_reveal(en, :EP) - println("energy_rank_reveal ", en) - println("----------------") add_edge!(fg, v, w) set_props!( fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) @@ -111,25 +89,6 @@ function factor_graph( factor_graph(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end -#= -function rank_reveal(energy, order=:PE) - @assert order ∈ (:PE, :EP) - dim = order == :PE ? 1 : 2 - - E, idx = unique_dims(energy, dim) - - if order == :PE - P = zeros(size(energy, 1), size(E, 1)) - else - P = zeros(size(E, 2), size(energy, 2)) - end - - for (i, elements) ∈ enumerate(eachslice(P, dims=dim)) - elements[idx[i]] = 1 - end - - order == :PE ? (P, E) : (E, P) -end=# function rank_reveal(energy, order=:PE) @assert order ∈ (:PE, :EP) diff --git a/test/runtests.jl b/test/runtests.jl index 8b42a4d..bd783a3 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -7,10 +7,7 @@ using Test Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) -my_tests = [ - #"ising.jl", "factor.jl", - "new_factor.jl" - ] +my_tests = ["ising.jl", "factor.jl"] for my_test ∈ my_tests include(my_test) From 3529b97200cc07909903233b257a7ab96d8c0a6f Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 20 Oct 2021 09:22:36 +0200 Subject: [PATCH 005/218] add ! in decode_projector --- src/factor.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 1835ffd..4e6b514 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -1,4 +1,4 @@ -export factor_graph, rank_reveal, projectors, split_into_clusters, decode_factor_graph_state, decode_projector +export factor_graph, rank_reveal, projectors, split_into_clusters, decode_factor_graph_state, decode_projector! function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} @@ -100,7 +100,7 @@ function rank_reveal(energy, order=:PE) end -function decode_projector(idx, order=:PE) +function decode_projector!(idx, order=:PE) @assert order ∈ (:PE, :EP) dim = order == :PE ? 1 : 2 if order == :PE From 87c574f95882cc04cf43c5cd6af03f4b225b7b23 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 20 Oct 2021 09:30:13 +0200 Subject: [PATCH 006/218] clean up --- test/factor.jl | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/test/factor.jl b/test/factor.jl index 6493d11..e8987f5 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -116,7 +116,7 @@ end end #@test energy ≈ pl * (en * pr) - @test energy ≈ decode_projector(pl, :PE) * (en * decode_projector(pr, :EP)) + @test energy ≈ decode_projector!(pl, :PE) * (en * decode_projector!(pr, :EP)) end @testset "each cluster comprises expected cells" begin @@ -140,7 +140,7 @@ end @testset "Rank reveal correctly decomposes energy row-wise" begin energy = [[1 2 3]; [0 -1 0]; [1 2 3]] PP, E = rank_reveal(energy, :PE) - P = decode_projector(PP, :PE) + P = decode_projector!(PP, :PE) @test length(PP) == 3 @test size(P) == (3, 2) @test size(E) == (2, 3) @@ -150,7 +150,7 @@ end @testset "Rank reveal correctly decomposes energy column-wise" begin energy = [[1, 2, 3] [0, -1, 1] [1, 2, 3]] E, PP = rank_reveal(energy, :EP) - P = decode_projector(PP, :EP) + P = decode_projector!(PP, :EP) @test length(PP) == 3 @test size(P) == (2, 3) @test size(E) == (3, 2) @@ -170,14 +170,14 @@ end [-1.0 0.5 -1.5 0.0 0.0 1.5 -0.5 1.0] ] PPl, E_old = rank_reveal(energy, :PE) - Pl = decode_projector(PPl, :PE) + Pl = decode_projector!(PPl, :PE) @test length(PPl) == 8 @test size(Pl) == (8, 8) @test size(E_old) == (8, 8) @test Pl * E_old ≈ energy E, PPr = rank_reveal(E_old, :EP) - Pr = decode_projector(PPr, :EP) + Pr = decode_projector!(PPr, :EP) @test length(PPr) == 8 @test size(Pr) == (8, 8) @test size(E) == (8, 8) @@ -290,7 +290,7 @@ function factor_graph_energy(fg, state) for edge ∈ edges(fg) i, j = fg.reverse_label_map[src(edge)], fg.reverse_label_map[dst(edge)] pl, en, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :en), get_prop(fg, edge, :pr) - edge_energy = decode_projector(pl, :PE) * en * decode_projector(pr, :EP) + edge_energy = decode_projector!(pl, :PE) * en * decode_projector!(pr, :EP) total_en += edge_energy[state[i], state[j]] end From 788e99603029f3b242342e35a6d2e94aace24d23 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 19 Nov 2021 15:44:35 +0100 Subject: [PATCH 007/218] forma and clean up code --- src/factor.jl | 42 +++++++++++------------------------------- src/ising.jl | 36 ++++++++++++++---------------------- src/lattice.jl | 6 +----- src/spectrum.jl | 12 ++++-------- src/states.jl | 5 ++--- 5 files changed, 32 insertions(+), 69 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 4e6b514..0b51500 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -1,5 +1,5 @@ -export factor_graph, rank_reveal, projectors, split_into_clusters, decode_factor_graph_state, decode_projector! - +export factor_graph, rank_reveal, projectors, split_into_clusters +export decode_factor_graph_state, decode_projector! function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} cluster_id_to_verts = Dict( @@ -15,27 +15,18 @@ function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, ) end - function factor_graph( - ig::IsingGraph, - num_states_cl::Int; - spectrum::Function=full_spectrum, + ig::IsingGraph, num_states_cl::Int; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} # e.g. square lattice ) where {T} ns = Dict(i => num_states_cl for i ∈ Set(values(cluster_assignment_rule))) factor_graph( - ig, - ns, - spectrum=spectrum, - cluster_assignment_rule=cluster_assignment_rule + ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule ) end - function factor_graph( - ig::IsingGraph, - num_states_cl::Dict{T, Int}; - spectrum::Function=full_spectrum, + ig::IsingGraph, num_states_cl::Dict{T, Int}; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} # e.g. square lattice ) where {T} L = maximum(values(cluster_assignment_rule)) @@ -61,15 +52,13 @@ function factor_graph( states_v = get_prop(fg, v, :spectrum).states states_w = get_prop(fg, w, :spectrum).states - reduced_states_v = [s[ind1] for s in states_v] - reduced_states_w = [s[ind2] for s in states_w] + reduced_states_v = [s[ind1] for s in states_v] + reduced_states_w = [s[ind2] for s in states_w] pl, unique_states_v = rank_reveal(reduced_states_v, :PE) pr, unique_states_w = rank_reveal(reduced_states_w, :PE) - - en = inter_cluster_energy( - unique_states_v, JJ, unique_states_w - ) + + en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) add_edge!(fg, v, w) set_props!( @@ -80,26 +69,20 @@ function factor_graph( fg end - function factor_graph( - ig::IsingGraph; - spectrum::Function=full_spectrum, - cluster_assignment_rule::Dict{Int, T} + ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} ) where {T} factor_graph(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end - function rank_reveal(energy, order=:PE) @assert order ∈ (:PE, :EP) dim = order == :PE ? 1 : 2 E, idx = unique_dims(energy, dim) P = identity.(idx) - order == :PE ? (P, E) : (E, P) end - function decode_projector!(idx, order=:PE) @assert order ∈ (:PE, :EP) dim = order == :PE ? 1 : 2 @@ -109,13 +92,10 @@ function decode_projector!(idx, order=:PE) P = zeros(maximum(idx), size(idx, 1)) end - for (i, elements) ∈ enumerate(eachslice(P, dims=dim)) - elements[idx[i]] = 1 - end + for (i, elements) ∈ enumerate(eachslice(P, dims=dim)) elements[idx[i]] = 1 end P end - function decode_factor_graph_state(fg, state::Vector{Int}) ret = Dict{Int, Int}() for (i, vert) ∈ zip(state, vertices(fg)) diff --git a/src/ising.jl b/src/ising.jl index c0a6378..ea67080 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -1,14 +1,15 @@ using LabelledGraphs -export ising_graph, rank_vec, cluster, rank, nodes, basis_size, biases, couplings, IsingGraph, prune +export ising_graph, rank_vec, cluster, rank, nodes, basis_size, biases, couplings +export IsingGraph, prune const Instance = Union{String, Dict} - - -unique_nodes(ising_tuples) = sort(collect(Set(Iterators.flatten((i, j) for (i, j, _) ∈ ising_tuples)))) - const IsingGraph = LabelledGraph{MetaGraph{Int64, Float64}, Int64} +function unique_nodes(ising_tuples) + sort(collect(Set(Iterators.flatten((i, j) for (i, j, _) ∈ ising_tuples)))) +end + """ $(TYPEDSIGNATURES) @@ -19,9 +20,7 @@ Create the Ising spin glass model. Store extra information """ function ising_graph( - instance::Instance; - sgn::Number=1.0, - rank_override::Dict{Int, Int}=Dict{Int, Int}() + instance::Instance; sgn::Number=1.0, rank_override::Dict{Int, Int}=Dict{Int, Int}() ) # load the Ising instance if instance isa String @@ -41,7 +40,6 @@ function ising_graph( for (i, j, v) ∈ ising v *= sgn - if i == j set_prop!(ig, i, :h, v) else @@ -50,15 +48,9 @@ function ising_graph( end end - set_prop!( - ig, - :rank, - Dict{Int, Int}( - v => get(rank_override, v, 2) for v in vertices(ig) - ) + ig, :rank, Dict{Int, Int}(v => get(rank_override, v, 2) for v in vertices(ig)) ) - ig end @@ -74,16 +66,13 @@ function couplings(ig::IsingGraph) end J end - cluster(ig::IsingGraph, verts) = induced_subgraph(ig, collect(verts)) function inter_cluster_edges(ig::IsingGraph, cl1::IsingGraph, cl2::IsingGraph) verts1, verts2 = vertices(cl1), vertices(cl2) outer_edges = [ - LabelledEdge(i, j) - for i ∈ vertices(cl1), j ∈ vertices(cl2) - if has_edge(ig, i, j) + LabelledEdge(i, j) for i ∈ vertices(cl1), j ∈ vertices(cl2) if has_edge(ig, i, j) ] J = zeros(nv(cl1), nv(cl2)) @@ -94,10 +83,13 @@ function inter_cluster_edges(ig::IsingGraph, cl1::IsingGraph, cl2::IsingGraph) outer_edges, J end -function prune(ig::IsingGraph) +function prune(ig::IsingGraph) to_keep = vcat( findall(!iszero, degree(ig)), - findall(x->iszero(degree(ig, x)) && !isapprox(get_prop(ig, x, :h), 0, atol=1e-14), vertices(ig)) + findall( + x->iszero(degree(ig, x)) && !isapprox(get_prop(ig, x, :h), 0, atol=1e-14), + vertices(ig) + ) ) gg = ig[ig.labels[to_keep]] diff --git a/src/lattice.jl b/src/lattice.jl index b14c378..3664bfe 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -3,11 +3,7 @@ export super_square_lattice function super_square_lattice(size::NTuple{5, Int}) m, um, n, un, t = size old = LinearIndices((1:t, 1:un, 1:n, 1:um, 1:m)) - - Dict( - old[k, uj, j, ui, i] => (i, j) - for i=1:m, ui=1:um, j=1:n, uj=1:un, k=1:t - ) + Dict(old[k, uj, j, ui, i] => (i, j) for i=1:m, ui=1:um, j=1:n, uj=1:un, k=1:t) end function super_square_lattice(size::NTuple{3, Int}) diff --git a/src/spectrum.jl b/src/spectrum.jl index 071d911..13c8d99 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -1,7 +1,4 @@ -export all_states, local_basis -export gibbs_tensor -export brute_force, full_spectrum, energy -export Spectrum +export all_states, local_basis, gibbs_tensor, brute_force, full_spectrum, energy, Spectrum """ $(TYPEDSIGNATURES) @@ -22,7 +19,6 @@ function gibbs_tensor(ig::IsingGraph, β=Float64=1.0) ρ ./ sum(ρ) end - """ $(TYPEDSIGNATURES) @@ -63,15 +59,15 @@ function brute_force(ig::IsingGraph; sorted=true, num_states::Int=1) end end -full_spectrum(ig::IsingGraph; num_states::Int=1) = brute_force(ig, sorted=false, num_states=num_states) +function full_spectrum(ig::IsingGraph; num_states::Int=1) + brute_force(ig, sorted=false, num_states=num_states) +end struct Spectrum energies::Vector{Float64} states::Vector{Vector{Int}} end -# Please don't make the below another energy method. -# There is already so much mess going on :) function inter_cluster_energy(cl1_states, J::Matrix, cl2_states) hcat(collect.(cl1_states)...)' * J * hcat(collect.(cl2_states)...) end diff --git a/src/states.jl b/src/states.jl index 8dd3544..9a4c107 100644 --- a/src/states.jl +++ b/src/states.jl @@ -1,5 +1,4 @@ -export idx -export local_basis +export idx, local_basis idx(σ::Int) = (σ == -1) ? 1 : σ + 1 local_basis(d::Int) = union(-1, 1:d-1) @@ -7,4 +6,4 @@ local_basis(d::Int) = union(-1, 1:d-1) function all_states(rank::Union{Vector, NTuple}) basis = [local_basis(r) for r ∈ rank] Iterators.product(basis...) -end \ No newline at end of file +end From 4c518db8f884e518b88929d0c636e155f1246050 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 19 Nov 2021 15:46:55 +0100 Subject: [PATCH 008/218] clean up more --- src/factor.jl | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 0b51500..9d8e363 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -38,9 +38,7 @@ function factor_graph( end for (i, v) ∈ enumerate(vertices(fg)), w ∈ vertices(fg)[i+1:end] - cl1, cl2 = get_prop(fg, v, :cluster), get_prop(fg, w, :cluster) - outer_edges, J = inter_cluster_edges(ig, cl1, cl2) if !isempty(outer_edges) @@ -72,7 +70,9 @@ end function factor_graph( ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} ) where {T} - factor_graph(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) + factor_graph( + ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule + ) end function rank_reveal(energy, order=:PE) From 89885c12818aedd2ae04b14c53b6c4e02244346f Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 19 Nov 2021 15:50:28 +0100 Subject: [PATCH 009/218] formate code --- src/factor.jl | 19 ++++--------------- src/ising.jl | 2 -- 2 files changed, 4 insertions(+), 17 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 9d8e363..53826e9 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -2,17 +2,9 @@ export factor_graph, rank_reveal, projectors, split_into_clusters export decode_factor_graph_state, decode_projector! function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} - cluster_id_to_verts = Dict( - i => T[] for i in values(assignment_rule) - ) - - for v in vertices(ig) - push!(cluster_id_to_verts[assignment_rule[v]], v) - end - - Dict( - i => first(cluster(ig, verts)) for (i, verts) ∈ cluster_id_to_verts - ) + cluster_id_to_verts = Dict(i => T[] for i in values(assignment_rule)) + for v in vertices(ig) push!(cluster_id_to_verts[assignment_rule[v]], v) end + Dict(i => first(cluster(ig, verts)) for (i, verts) ∈ cluster_id_to_verts) end function factor_graph( @@ -20,9 +12,7 @@ function factor_graph( cluster_assignment_rule::Dict{Int, T} # e.g. square lattice ) where {T} ns = Dict(i => num_states_cl for i ∈ Set(values(cluster_assignment_rule))) - factor_graph( - ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule - ) + factor_graph(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end function factor_graph( @@ -55,7 +45,6 @@ function factor_graph( pl, unique_states_v = rank_reveal(reduced_states_v, :PE) pr, unique_states_w = rank_reveal(reduced_states_w, :PE) - en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) add_edge!(fg, v, w) diff --git a/src/ising.jl b/src/ising.jl index ea67080..9ec5407 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -53,7 +53,6 @@ function ising_graph( ) ig end - rank_vec(ig::IsingGraph) = Int[get_prop((ig), v, :rank) for v ∈ vertices(ig)] basis_size(ig::IsingGraph) = prod(prod(rank_vec(ig))) biases(ig::IsingGraph) = get_prop.(Ref(ig), vertices(ig), :h) @@ -91,7 +90,6 @@ function prune(ig::IsingGraph) vertices(ig) ) ) - gg = ig[ig.labels[to_keep]] labels = collect(vertices(gg.inner_graph)) reverse_label_map = Dict(i => i for i=1:nv(gg.inner_graph)) From 46c8e3010f58175fddc852141a01002859af8bef Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 2 Dec 2021 16:34:21 +0100 Subject: [PATCH 010/218] clean up --- src/factor.jl | 10 +++++++--- src/ising.jl | 2 +- src/spectrum.jl | 2 +- 3 files changed, 9 insertions(+), 5 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 53826e9..f47b02c 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -8,7 +8,9 @@ function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, end function factor_graph( - ig::IsingGraph, num_states_cl::Int; spectrum::Function=full_spectrum, + ig::IsingGraph, + num_states_cl::Int; + spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} # e.g. square lattice ) where {T} ns = Dict(i => num_states_cl for i ∈ Set(values(cluster_assignment_rule))) @@ -16,8 +18,10 @@ function factor_graph( end function factor_graph( - ig::IsingGraph, num_states_cl::Dict{T, Int}; spectrum::Function=full_spectrum, - cluster_assignment_rule::Dict{Int, T} # e.g. square lattice + ig::IsingGraph, + num_states_cl::Dict{T, Int}; + spectrum::Function=full_spectrum, + cluster_assignment_rule::Dict{Int, T} ) where {T} L = maximum(values(cluster_assignment_rule)) fg = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) diff --git a/src/ising.jl b/src/ising.jl index 9ec5407..899a14d 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -26,7 +26,7 @@ function ising_graph( if instance isa String ising = CSV.File(instance, types = [Int, Int, Float64], header=0, comment = "#") else - ising = [ (i, j, J) for ((i, j), J) ∈ instance ] + ising = [(i, j, J) for ((i, j), J) ∈ instance] end nodes = unique_nodes(ising) diff --git a/src/spectrum.jl b/src/spectrum.jl index 13c8d99..b27c5d4 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -13,7 +13,7 @@ Calculates matrix elements (probabilities) of \$\\rho\$ ``` for all possible configurations \$\\σ\$. """ -function gibbs_tensor(ig::IsingGraph, β=Float64=1.0) +function gibbs_tensor(ig::IsingGraph, β::Real=1.0) states = collect.(all_states(rank_vec(ig))) ρ = exp.(-β .* energy.(states, Ref(ig))) ρ ./ sum(ρ) From 26e18659bae8187ce73f2f2a1890c32a1783aec3 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 3 Dec 2021 10:00:40 +0100 Subject: [PATCH 011/218] add test full_pegasus --- src/spectrum.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/spectrum.jl b/src/spectrum.jl index b27c5d4..78ddf71 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -49,8 +49,8 @@ function brute_force(ig::IsingGraph; sorted=true, num_states::Int=1) ig_rank = rank_vec(ig) num_states = min(num_states, prod(ig_rank)) - σ = collect.(all_states(ig_rank)) - energies = energy.(σ, Ref(ig)) + @time σ = collect.(all_states(ig_rank)) + @time energies = energy.(σ, Ref(ig)) if sorted perm = partialsortperm(vec(energies), 1:num_states) return Spectrum(energies[perm], σ[perm]) From fed72d34ef6a7abff0e805f8b0117d3c575aef02 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 3 Dec 2021 10:47:21 +0100 Subject: [PATCH 012/218] brodcast all_states --- src/states.jl | 5 +---- test/spectrum.jl | 23 +++++++++++++++++++++++ 2 files changed, 24 insertions(+), 4 deletions(-) create mode 100644 test/spectrum.jl diff --git a/src/states.jl b/src/states.jl index 9a4c107..6584397 100644 --- a/src/states.jl +++ b/src/states.jl @@ -3,7 +3,4 @@ export idx, local_basis idx(σ::Int) = (σ == -1) ? 1 : σ + 1 local_basis(d::Int) = union(-1, 1:d-1) -function all_states(rank::Union{Vector, NTuple}) - basis = [local_basis(r) for r ∈ rank] - Iterators.product(basis...) -end +all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank)...) diff --git a/test/spectrum.jl b/test/spectrum.jl new file mode 100644 index 0000000..873d795 --- /dev/null +++ b/test/spectrum.jl @@ -0,0 +1,23 @@ +@testset "Factor graph builds on pathological instance" begin + m = 3 + n = 4 + t = 3 + + β = 1. + + L = n * m * t + max_cl_states = 20 + + instance = "$(@__DIR__)/instances/pathological/cross_$(m)_$(n)_dd.txt" + ig = ising_graph(instance) + + fg = factor_graph( + ig, + max_cl_states, + spectrum=brute_force, + cluster_assignment_rule=super_square_lattice((m, n, t)) + ) + + @time sp = brute_force(ig; sorted=true, num_states=states) + +end From e52b042b010635e4792b288e74f4934fe675dc38 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 3 Dec 2021 11:48:03 +0100 Subject: [PATCH 013/218] add instances and example for Lukasz --- src/SpinGlassNetworks.jl | 1 - src/spectrum.jl | 47 +- src/states.jl | 6 - test/instances/pegasus_droplets/2_2_3_00.txt | 583 ++++ test/instances/pegasus_droplets/3_3_3_00.txt | 1435 +++++++++ test/instances/pegasus_droplets/4_4_3_00.txt | 2660 ++++++++++++++++ test/instances/pegasus_droplets/test_2_2.txt | 624 ++++ test/instances/pegasus_droplets/test_3_3.txt | 1540 ++++++++++ test/instances/pegasus_droplets/test_4_4.txt | 2864 ++++++++++++++++++ test/new_factor.jl | 22 - test/spectrum.jl | 20 +- 11 files changed, 9722 insertions(+), 80 deletions(-) delete mode 100644 src/states.jl create mode 100644 test/instances/pegasus_droplets/2_2_3_00.txt create mode 100644 test/instances/pegasus_droplets/3_3_3_00.txt create mode 100644 test/instances/pegasus_droplets/4_4_3_00.txt create mode 100644 test/instances/pegasus_droplets/test_2_2.txt create mode 100644 test/instances/pegasus_droplets/test_3_3.txt create mode 100644 test/instances/pegasus_droplets/test_4_4.txt delete mode 100644 test/new_factor.jl diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index e88c5c2..9b53166 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -84,7 +84,6 @@ module SpinGlassNetworks end end - include("states.jl") include("ising.jl") include("spectrum.jl") include("lattice.jl") diff --git a/src/spectrum.jl b/src/spectrum.jl index 78ddf71..80cf573 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -1,61 +1,32 @@ -export all_states, local_basis, gibbs_tensor, brute_force, full_spectrum, energy, Spectrum +export all_states, local_basis, gibbs_tensor, brute_force +export full_spectrum, energy, Spectrum, idx, local_basis -""" -$(TYPEDSIGNATURES) +idx(σ::Int) = (σ == -1) ? 1 : σ + 1 +local_basis(d::Int) = union(-1, 1:d-1) +all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank)...) -Calculates Gibbs state of a classical Ising Hamiltonian - -# Details - -Calculates matrix elements (probabilities) of \$\\rho\$ -```math -\$\\bra{\\σ}\\rho\\ket{\\sigma}\$ -``` -for all possible configurations \$\\σ\$. -""" function gibbs_tensor(ig::IsingGraph, β::Real=1.0) states = collect.(all_states(rank_vec(ig))) ρ = exp.(-β .* energy.(states, Ref(ig))) ρ ./ sum(ρ) end -""" -$(TYPEDSIGNATURES) - -Calculate the Ising energy -```math -E = -\\sum_ s_i J_{ij} * s_j - \\sum_j h_i s_j. -``` -""" energy(σ::Vector, J::Matrix, η::Vector=σ) = dot(σ, J, η) energy(σ::Vector, h::Vector) = dot(h, σ) energy(σ::Vector, ig::IsingGraph) = energy(σ, couplings(ig)) + energy(σ, biases(ig)) - -""" -$(TYPEDSIGNATURES) - -Return the low energy spectrum - -# Details - -Calculates \$k\$ lowest energy states -together with the coresponding energies -of a classical Ising Hamiltonian -""" - function brute_force(ig::IsingGraph; sorted=true, num_states::Int=1) - if nv(ig) == 0 return Spectrum(zeros(1), []) end + if nv(ig) == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end ig_rank = rank_vec(ig) num_states = min(num_states, prod(ig_rank)) - @time σ = collect.(all_states(ig_rank)) - @time energies = energy.(σ, Ref(ig)) + σ = collect.(all_states(ig_rank)) + energies = energy.(σ, Ref(ig)) if sorted perm = partialsortperm(vec(energies), 1:num_states) return Spectrum(energies[perm], σ[perm]) else - return Spectrum(energies[1:num_states], σ[1:num_states]) + return Spectrum(energies[begin:num_states], σ[begin:num_states]) end end diff --git a/src/states.jl b/src/states.jl deleted file mode 100644 index 6584397..0000000 --- a/src/states.jl +++ /dev/null @@ -1,6 +0,0 @@ -export idx, local_basis - -idx(σ::Int) = (σ == -1) ? 1 : σ + 1 -local_basis(d::Int) = union(-1, 1:d-1) - -all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank)...) diff --git a/test/instances/pegasus_droplets/2_2_3_00.txt b/test/instances/pegasus_droplets/2_2_3_00.txt new file mode 100644 index 0000000..ff853a5 --- /dev/null +++ b/test/instances/pegasus_droplets/2_2_3_00.txt @@ -0,0 +1,583 @@ +# +1 1 0.031250 +2 2 0.031250 +3 3 -0.031250 +4 4 -0.031250 +5 5 -0.062500 +6 6 0.031250 +8 8 0.031250 +9 9 0.062500 +10 10 0.031250 +11 11 -0.062500 +12 12 -0.062500 +14 14 -0.062500 +16 16 -0.062500 +17 17 -0.031250 +18 18 -0.062500 +19 19 0.031250 +20 20 -0.031250 +22 22 0.031250 +23 23 -0.031250 +24 24 0.031250 +25 25 0.031250 +26 26 0.031250 +28 28 -0.031250 +29 29 -0.062500 +30 30 -0.062500 +32 32 -0.062500 +33 33 0.062500 +34 34 0.062500 +35 35 -0.031250 +36 36 0.031250 +38 38 0.031250 +39 39 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instance" begin - m = 3 - n = 4 - t = 3 - - β = 1. - - schedule = 1. - - L = n * m * t - states_to_keep = 20 - - instance = "$(@__DIR__)/instances/pathological/cross_$(m)_$(n)_dd.txt" - ig = ising_graph(instance) - - fg = factor_graph( - ig, - spectrum=full_spectrum, - cluster_assignment_rule=super_square_lattice((m, n, t)) - ) - -end \ No newline at end of file diff --git a/test/spectrum.jl b/test/spectrum.jl index 873d795..ceca975 100644 --- a/test/spectrum.jl +++ b/test/spectrum.jl @@ -1,23 +1,17 @@ -@testset "Factor graph builds on pathological instance" begin + +function bench(instance::String) m = 3 n = 4 t = 3 + max_cl_states = 100 - β = 1. - - L = n * m * t - max_cl_states = 20 - - instance = "$(@__DIR__)/instances/pathological/cross_$(m)_$(n)_dd.txt" - ig = ising_graph(instance) - - fg = factor_graph( + @time ig = ising_graph(instance) + @time fg = factor_graph( ig, max_cl_states, spectrum=brute_force, cluster_assignment_rule=super_square_lattice((m, n, t)) ) - - @time sp = brute_force(ig; sorted=true, num_states=states) - end + +bench("$(@__DIR__)/instances/pegasus_droplets/2_2_3_00.txt") From 5f2841ed706f549f48173c4bac17f7eed7ce2d82 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 3 Dec 2021 11:51:42 +0100 Subject: [PATCH 014/218] add benchmarks --- .../pegasus_droplets/2_2_3_00.txt | 0 .../pegasus_droplets/3_3_3_00.txt | 0 .../pegasus_droplets/4_4_3_00.txt | 0 .../pegasus_droplets/test_2_2.txt | 0 .../pegasus_droplets/test_3_3.txt | 0 .../pegasus_droplets/test_4_4.txt | 0 {test => benchmarks}/spectrum.jl | 9 ++++++--- 7 files changed, 6 insertions(+), 3 deletions(-) rename {test/instances => benchmarks}/pegasus_droplets/2_2_3_00.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/3_3_3_00.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/4_4_3_00.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/test_2_2.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/test_3_3.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/test_4_4.txt (100%) rename {test => benchmarks}/spectrum.jl (73%) diff --git a/test/instances/pegasus_droplets/2_2_3_00.txt b/benchmarks/pegasus_droplets/2_2_3_00.txt similarity index 100% rename from test/instances/pegasus_droplets/2_2_3_00.txt rename to benchmarks/pegasus_droplets/2_2_3_00.txt diff --git a/test/instances/pegasus_droplets/3_3_3_00.txt b/benchmarks/pegasus_droplets/3_3_3_00.txt similarity index 100% rename from test/instances/pegasus_droplets/3_3_3_00.txt rename to benchmarks/pegasus_droplets/3_3_3_00.txt diff --git a/test/instances/pegasus_droplets/4_4_3_00.txt b/benchmarks/pegasus_droplets/4_4_3_00.txt similarity index 100% rename from test/instances/pegasus_droplets/4_4_3_00.txt rename to benchmarks/pegasus_droplets/4_4_3_00.txt diff --git a/test/instances/pegasus_droplets/test_2_2.txt b/benchmarks/pegasus_droplets/test_2_2.txt similarity index 100% rename from test/instances/pegasus_droplets/test_2_2.txt rename to benchmarks/pegasus_droplets/test_2_2.txt diff --git a/test/instances/pegasus_droplets/test_3_3.txt b/benchmarks/pegasus_droplets/test_3_3.txt similarity index 100% rename from test/instances/pegasus_droplets/test_3_3.txt rename to benchmarks/pegasus_droplets/test_3_3.txt diff --git a/test/instances/pegasus_droplets/test_4_4.txt b/benchmarks/pegasus_droplets/test_4_4.txt similarity index 100% rename from test/instances/pegasus_droplets/test_4_4.txt rename to benchmarks/pegasus_droplets/test_4_4.txt diff --git a/test/spectrum.jl b/benchmarks/spectrum.jl similarity index 73% rename from test/spectrum.jl rename to benchmarks/spectrum.jl index ceca975..fdda287 100644 --- a/test/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -1,11 +1,14 @@ +using SpinGlassNetworks + function bench(instance::String) - m = 3 - n = 4 + m = 2 + n = 2 t = 3 max_cl_states = 100 @time ig = ising_graph(instance) + @time fg = factor_graph( ig, max_cl_states, @@ -14,4 +17,4 @@ function bench(instance::String) ) end -bench("$(@__DIR__)/instances/pegasus_droplets/2_2_3_00.txt") +bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt") From 1a608b8f1fa26720528ec8a22769ef4ebe37322d Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 3 Dec 2021 11:52:16 +0100 Subject: [PATCH 015/218] correct a type --- benchmarks/spectrum.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index fdda287..10b0d49 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -4,7 +4,7 @@ using SpinGlassNetworks function bench(instance::String) m = 2 n = 2 - t = 3 + t = 24 max_cl_states = 100 @time ig = ising_graph(instance) From d915c2cbe6d3bfdcfa13ed3e7a861c7b4414124f Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 3 Dec 2021 12:11:27 +0100 Subject: [PATCH 016/218] clean up --- src/factor.jl | 7 ++++--- src/ising.jl | 13 ++----------- test/factor.jl | 12 ++++++------ .../instances}/pegasus_droplets/2_2_3_00.txt | 0 .../instances}/pegasus_droplets/3_3_3_00.txt | 0 .../instances}/pegasus_droplets/4_4_3_00.txt | 0 .../instances}/pegasus_droplets/test_2_2.txt | 0 .../instances}/pegasus_droplets/test_3_3.txt | 0 .../instances}/pegasus_droplets/test_4_4.txt | 0 9 files changed, 12 insertions(+), 20 deletions(-) rename {benchmarks => test/instances}/pegasus_droplets/2_2_3_00.txt (100%) rename {benchmarks => test/instances}/pegasus_droplets/3_3_3_00.txt (100%) rename {benchmarks => test/instances}/pegasus_droplets/4_4_3_00.txt (100%) rename {benchmarks => test/instances}/pegasus_droplets/test_2_2.txt (100%) rename {benchmarks => test/instances}/pegasus_droplets/test_3_3.txt (100%) rename {benchmarks => test/instances}/pegasus_droplets/test_4_4.txt (100%) diff --git a/src/factor.jl b/src/factor.jl index f47b02c..4a04b7e 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -12,7 +12,7 @@ function factor_graph( num_states_cl::Int; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} # e.g. square lattice -) where {T} +) where T ns = Dict(i => num_states_cl for i ∈ Set(values(cluster_assignment_rule))) factor_graph(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end @@ -22,7 +22,7 @@ function factor_graph( num_states_cl::Dict{T, Int}; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} -) where {T} +) where T L = maximum(values(cluster_assignment_rule)) fg = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) @@ -62,7 +62,7 @@ end function factor_graph( ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} -) where {T} +) where T factor_graph( ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule ) @@ -76,6 +76,7 @@ function rank_reveal(energy, order=:PE) order == :PE ? (P, E) : (E, P) end +# to be removed function decode_projector!(idx, order=:PE) @assert order ∈ (:PE, :EP) dim = order == :PE ? 1 : 2 diff --git a/src/ising.jl b/src/ising.jl index 899a14d..86d5add 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -10,15 +10,6 @@ function unique_nodes(ising_tuples) sort(collect(Set(Iterators.flatten((i, j) for (i, j, _) ∈ ising_tuples)))) end -""" -$(TYPEDSIGNATURES) - -Create the Ising spin glass model. - -# Details - -Store extra information -""" function ising_graph( instance::Instance; sgn::Number=1.0, rank_override::Dict{Int, Int}=Dict{Int, Int}() ) @@ -61,7 +52,7 @@ function couplings(ig::IsingGraph) J = zeros(nv(ig), nv(ig)) for edge in edges(ig) i, j = ig.reverse_label_map[src(edge)], ig.reverse_label_map[dst(edge)] - J[i, j] = get_prop(ig, edge, :J) + @inbounds J[i, j] = get_prop(ig, edge, :J) end J end @@ -86,7 +77,7 @@ function prune(ig::IsingGraph) to_keep = vcat( findall(!iszero, degree(ig)), findall( - x->iszero(degree(ig, x)) && !isapprox(get_prop(ig, x, :h), 0, atol=1e-14), + x -> iszero(degree(ig, x)) && !isapprox(get_prop(ig, x, :h), 0, atol=1e-14), vertices(ig) ) ) diff --git a/test/factor.jl b/test/factor.jl index e8987f5..65efd9c 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -115,8 +115,8 @@ end end end - #@test energy ≈ pl * (en * pr) - @test energy ≈ decode_projector!(pl, :PE) * (en * decode_projector!(pr, :EP)) + @test energy ≈ pl * (en * pr) + #@test energy ≈ decode_projector!(pl, :PE) * (en * decode_projector!(pr, :EP)) end @testset "each cluster comprises expected cells" begin @@ -191,7 +191,7 @@ function create_example_factor_graph() h1 = 0.5 h2 = 0.75 - + D = Dict((1, 2) => J12, (1, 1) => h1, (2, 2) => h2) ig = ising_graph(D) @@ -209,7 +209,7 @@ const fg_state_to_spin = [ @testset "Decoding solution gives correct spin assignment" begin fg = create_example_factor_graph() - for (state, spin_values) ∈ fg_state_to_spin + for (state, spin_values) ∈ fg_state_to_spin d = decode_factor_graph_state(fg, state) states = collect(values(d))[collect(keys(d))] @test states == spin_values @@ -272,7 +272,7 @@ function create_larger_example_factor_graph() spectrum = full_spectrum, cluster_assignment_rule = assignment_rule, ) - + ig, fg end @@ -312,4 +312,4 @@ end end @test factor_graph_energy(fg, state) ≈ energy(spins, ig) end -end \ No newline at end of file +end diff --git a/benchmarks/pegasus_droplets/2_2_3_00.txt b/test/instances/pegasus_droplets/2_2_3_00.txt similarity index 100% rename from benchmarks/pegasus_droplets/2_2_3_00.txt rename to test/instances/pegasus_droplets/2_2_3_00.txt diff --git a/benchmarks/pegasus_droplets/3_3_3_00.txt b/test/instances/pegasus_droplets/3_3_3_00.txt similarity index 100% rename from benchmarks/pegasus_droplets/3_3_3_00.txt rename to test/instances/pegasus_droplets/3_3_3_00.txt diff --git a/benchmarks/pegasus_droplets/4_4_3_00.txt b/test/instances/pegasus_droplets/4_4_3_00.txt similarity index 100% rename from benchmarks/pegasus_droplets/4_4_3_00.txt rename to test/instances/pegasus_droplets/4_4_3_00.txt diff --git a/benchmarks/pegasus_droplets/test_2_2.txt b/test/instances/pegasus_droplets/test_2_2.txt similarity index 100% rename from benchmarks/pegasus_droplets/test_2_2.txt rename to test/instances/pegasus_droplets/test_2_2.txt diff --git a/benchmarks/pegasus_droplets/test_3_3.txt b/test/instances/pegasus_droplets/test_3_3.txt similarity index 100% rename from benchmarks/pegasus_droplets/test_3_3.txt rename to test/instances/pegasus_droplets/test_3_3.txt diff --git a/benchmarks/pegasus_droplets/test_4_4.txt b/test/instances/pegasus_droplets/test_4_4.txt similarity index 100% rename from benchmarks/pegasus_droplets/test_4_4.txt rename to test/instances/pegasus_droplets/test_4_4.txt From 4a8d87628005655ed387900375a202d4d6baa864 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 3 Dec 2021 12:12:30 +0100 Subject: [PATCH 017/218] correct typo --- test/factor.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/test/factor.jl b/test/factor.jl index 65efd9c..e57c4ef 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -115,8 +115,8 @@ end end end - @test energy ≈ pl * (en * pr) - #@test energy ≈ decode_projector!(pl, :PE) * (en * decode_projector!(pr, :EP)) + #@test energy ≈ pl * (en * pr) + @test energy ≈ decode_projector!(pl, :PE) * (en * decode_projector!(pr, :EP)) end @testset "each cluster comprises expected cells" begin From 80ac202f07bf9d0fe8c543b563c998cf867aebc6 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 3 Dec 2021 14:55:04 +0100 Subject: [PATCH 018/218] simplify spectrum.jl --- .../pegasus_droplets/2_2_3_00.txt | 0 .../pegasus_droplets/3_3_3_00.txt | 0 .../pegasus_droplets/4_4_3_00.txt | 0 .../pegasus_droplets/test_2_2.txt | 0 .../pegasus_droplets/test_3_3.txt | 0 .../pegasus_droplets/test_4_4.txt | 0 benchmarks/spectrum.jl | 10 ++-------- src/ising.jl | 2 +- 8 files changed, 3 insertions(+), 9 deletions(-) rename {test/instances => benchmarks}/pegasus_droplets/2_2_3_00.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/3_3_3_00.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/4_4_3_00.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/test_2_2.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/test_3_3.txt (100%) rename {test/instances => benchmarks}/pegasus_droplets/test_4_4.txt (100%) diff --git a/test/instances/pegasus_droplets/2_2_3_00.txt b/benchmarks/pegasus_droplets/2_2_3_00.txt similarity index 100% rename from test/instances/pegasus_droplets/2_2_3_00.txt rename to benchmarks/pegasus_droplets/2_2_3_00.txt diff --git a/test/instances/pegasus_droplets/3_3_3_00.txt b/benchmarks/pegasus_droplets/3_3_3_00.txt similarity index 100% rename from test/instances/pegasus_droplets/3_3_3_00.txt rename to benchmarks/pegasus_droplets/3_3_3_00.txt diff --git a/test/instances/pegasus_droplets/4_4_3_00.txt b/benchmarks/pegasus_droplets/4_4_3_00.txt similarity index 100% rename from test/instances/pegasus_droplets/4_4_3_00.txt rename to benchmarks/pegasus_droplets/4_4_3_00.txt diff --git a/test/instances/pegasus_droplets/test_2_2.txt b/benchmarks/pegasus_droplets/test_2_2.txt similarity index 100% rename from test/instances/pegasus_droplets/test_2_2.txt rename to benchmarks/pegasus_droplets/test_2_2.txt diff --git a/test/instances/pegasus_droplets/test_3_3.txt b/benchmarks/pegasus_droplets/test_3_3.txt similarity index 100% rename from test/instances/pegasus_droplets/test_3_3.txt rename to benchmarks/pegasus_droplets/test_3_3.txt diff --git a/test/instances/pegasus_droplets/test_4_4.txt b/benchmarks/pegasus_droplets/test_4_4.txt similarity index 100% rename from test/instances/pegasus_droplets/test_4_4.txt rename to benchmarks/pegasus_droplets/test_4_4.txt diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 10b0d49..8406dac 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -5,16 +5,10 @@ function bench(instance::String) m = 2 n = 2 t = 24 - max_cl_states = 100 @time ig = ising_graph(instance) - - @time fg = factor_graph( - ig, - max_cl_states, - spectrum=brute_force, - cluster_assignment_rule=super_square_lattice((m, n, t)) - ) + @time cl = split_into_clusters(ig, super_square_lattice((m, n, t))) + @time brute_force(cl[1, 1], num_states=100) end bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt") diff --git a/src/ising.jl b/src/ising.jl index 86d5add..d90b6cf 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -11,7 +11,7 @@ function unique_nodes(ising_tuples) end function ising_graph( - instance::Instance; sgn::Number=1.0, rank_override::Dict{Int, Int}=Dict{Int, Int}() + instance::Instance; sgn::Real=1.0, rank_override::Dict{Int, Int}=Dict{Int, Int}() ) # load the Ising instance if instance isa String From 1355ae3b23e0a2b011eac221f70f990cbe6e8b92 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 3 Dec 2021 21:01:15 +0100 Subject: [PATCH 019/218] remove decode_projector --- src/factor.jl | 16 +------------- test/factor.jl | 57 ++------------------------------------------------ 2 files changed, 3 insertions(+), 70 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 4a04b7e..660b580 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -1,5 +1,5 @@ export factor_graph, rank_reveal, projectors, split_into_clusters -export decode_factor_graph_state, decode_projector! +export decode_factor_graph_state function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} cluster_id_to_verts = Dict(i => T[] for i in values(assignment_rule)) @@ -76,20 +76,6 @@ function rank_reveal(energy, order=:PE) order == :PE ? (P, E) : (E, P) end -# to be removed -function decode_projector!(idx, order=:PE) - @assert order ∈ (:PE, :EP) - dim = order == :PE ? 1 : 2 - if order == :PE - P = zeros(size(idx, 1), maximum(idx)) - else - P = zeros(maximum(idx), size(idx, 1)) - end - - for (i, elements) ∈ enumerate(eachslice(P, dims=dim)) elements[idx[i]] = 1 end - P -end - function decode_factor_graph_state(fg, state::Vector{Int}) ret = Dict{Int, Int}() for (i, vert) ∈ zip(state, vertices(fg)) diff --git a/test/factor.jl b/test/factor.jl index e57c4ef..b0794f1 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -114,9 +114,7 @@ end energy[ii, jj] = eij end end - - #@test energy ≈ pl * (en * pr) - @test energy ≈ decode_projector!(pl, :PE) * (en * decode_projector!(pr, :EP)) + @test energy ≈ en[pl, pr] end @testset "each cluster comprises expected cells" begin @@ -136,62 +134,11 @@ end end end - -@testset "Rank reveal correctly decomposes energy row-wise" begin - energy = [[1 2 3]; [0 -1 0]; [1 2 3]] - PP, E = rank_reveal(energy, :PE) - P = decode_projector!(PP, :PE) - @test length(PP) == 3 - @test size(P) == (3, 2) - @test size(E) == (2, 3) - @test P * E ≈ energy -end - -@testset "Rank reveal correctly decomposes energy column-wise" begin - energy = [[1, 2, 3] [0, -1, 1] [1, 2, 3]] - E, PP = rank_reveal(energy, :EP) - P = decode_projector!(PP, :EP) - @test length(PP) == 3 - @test size(P) == (2, 3) - @test size(E) == (3, 2) - @test E * P ≈ energy -end - -@testset "Rank reveal correctly decomposes energy into projector, energy, projector" begin - #energy = [[1 2 3]; [0 -1 0]; [1 2 3]] - energy = [ - [1.0 -0.5 1.5 0.0 0.0 -1.5 0.5 -1.0]; - [0.0 0.5 0.5 1.0 -1.0 -0.5 -0.5 0.0]; - [0.5 0.0 1.0 0.5 -0.5 -1.0 0.0 -0.5]; - [-0.5 1.0 0.0 1.5 -1.5 0.0 -1.0 0.5]; - [0.5 -1.0 0.0 -1.5 1.5 0.0 1.0 -0.5]; - [-0.5 0.0 -1.0 -0.5 0.5 1.0 0.0 0.5]; - [0.0 -0.5 -0.5 -1.0 1.0 0.5 0.5 0.0]; - [-1.0 0.5 -1.5 0.0 0.0 1.5 -0.5 1.0] - ] - PPl, E_old = rank_reveal(energy, :PE) - Pl = decode_projector!(PPl, :PE) - @test length(PPl) == 8 - @test size(Pl) == (8, 8) - @test size(E_old) == (8, 8) - @test Pl * E_old ≈ energy - - E, PPr = rank_reveal(E_old, :EP) - Pr = decode_projector!(PPr, :EP) - @test length(PPr) == 8 - @test size(Pr) == (8, 8) - @test size(E) == (8, 8) - @test E * Pr ≈ E_old - @test Pl * E * Pr ≈ energy -end - - function create_example_factor_graph() J12 = -1.0 h1 = 0.5 h2 = 0.75 - D = Dict((1, 2) => J12, (1, 1) => h1, (2, 2) => h2) ig = ising_graph(D) @@ -290,7 +237,7 @@ function factor_graph_energy(fg, state) for edge ∈ edges(fg) i, j = fg.reverse_label_map[src(edge)], fg.reverse_label_map[dst(edge)] pl, en, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :en), get_prop(fg, edge, :pr) - edge_energy = decode_projector!(pl, :PE) * en * decode_projector!(pr, :EP) + edge_energy = en[pl, pr] total_en += edge_energy[state[i], state[j]] end From 18e017fd4cd7bf73eefa47b907cf682cba6f8071 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sat, 4 Dec 2021 17:38:04 +0100 Subject: [PATCH 020/218] threaded spectrum works --- benchmarks/spectrum.jl | 8 ++-- src/spectrum.jl | 98 +++++++++++++++++++++++++++++++----------- test/factor.jl | 2 +- test/ising.jl | 13 ++++-- test/runtests.jl | 5 +++ 5 files changed, 92 insertions(+), 34 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 8406dac..358748c 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -6,9 +6,9 @@ function bench(instance::String) n = 2 t = 24 - @time ig = ising_graph(instance) - @time cl = split_into_clusters(ig, super_square_lattice((m, n, t))) - @time brute_force(cl[1, 1], num_states=100) + ig = ising_graph(instance) + cl = split_into_clusters(ig, super_square_lattice((m, n, t))) + @time sp = brute_force(cl[1, 1], num_states=100) end -bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt") +bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); diff --git a/src/spectrum.jl b/src/spectrum.jl index 80cf573..fa94ea9 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -1,42 +1,90 @@ export all_states, local_basis, gibbs_tensor, brute_force -export full_spectrum, energy, Spectrum, idx, local_basis +export full_spectrum, Spectrum, idx, local_basis, energy -idx(σ::Int) = (σ == -1) ? 1 : σ + 1 local_basis(d::Int) = union(-1, 1:d-1) all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank)...) -function gibbs_tensor(ig::IsingGraph, β::Real=1.0) - states = collect.(all_states(rank_vec(ig))) - ρ = exp.(-β .* energy.(states, Ref(ig))) - ρ ./ sum(ρ) +struct Spectrum + energies::Vector{Float64} + states::Vector{Vector{Int}} end -energy(σ::Vector, J::Matrix, η::Vector=σ) = dot(σ, J, η) -energy(σ::Vector, h::Vector) = dot(h, σ) -energy(σ::Vector, ig::IsingGraph) = energy(σ, couplings(ig)) + energy(σ, biases(ig)) +function Spectrum(ig::IsingGraph) + L = nv(ig) + N = 2^L -function brute_force(ig::IsingGraph; sorted=true, num_states::Int=1) - if nv(ig) == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end - ig_rank = rank_vec(ig) - num_states = min(num_states, prod(ig_rank)) + energies = zeros(Float64, N) + states = Vector{Vector{Int}}(undef, N) - σ = collect.(all_states(ig_rank)) - energies = energy.(σ, Ref(ig)) - if sorted - perm = partialsortperm(vec(energies), 1:num_states) - return Spectrum(energies[perm], σ[perm]) - else - return Spectrum(energies[begin:num_states], σ[begin:num_states]) + J, h = couplings(ig), biases(ig) + Threads.@threads for i = 0:N-1 + σ = 2 .* digits(i, base=2, pad=L) .- 1 + @inbounds energies[i+1] = dot(σ, J, σ) + dot(h, σ) + @inbounds states[i+1] = σ end + Spectrum(energies, states) end -function full_spectrum(ig::IsingGraph; num_states::Int=1) - brute_force(ig, sorted=false, num_states=num_states) +#= +function _kernel( + energies, states, J, h +) + L = size(J, 1) + + i = (blockIdx().x - 1) * blockDim().x + threadIdx().x + σ = 2 .* digits(i, base=2, pad=L) .- 1 + @inbounds energies[i] = dot(σ, J, σ) + dot(h, σ) + @inbounds states[i] = σ + nothing end -struct Spectrum - energies::Vector{Float64} - states::Vector{Vector{Int}} +function CUDASpectrum(ig::IsingGraph) + L = nv(ig) + N = 2^L + + en_d = CUDA.zeros(Float64, N) + st_d = CUDA.Vector{Vector{Int}}(undef, N) + J_d, h_d = CUDA.zeros(L, L), CUDA.zeros(L) + + copyto!(couplings(ig), J_d) + copyto!(biases(ig), h_d) + + nb = ceil(Int, N/256) + CUDA.@sync begin + @cuda threads=N blocks=nb _kernel(en_d, st_d, J_d, h_d) + end + Spectrum(Array(en_d), Array(st_d)) +end +=# + +function energy( + σ::AbstractArray{Vector{Int}}, J::Matrix{<:Real}, h::Vector{<:Real} +) + dot.(σ, Ref(J), σ) + dot.(Ref(h), σ) +end + +function gibbs_tensor(ig::IsingGraph, β::Real=1.0) + σ = collect.(all_states(rank_vec(ig))) + ρ = exp.(-β .* energy(σ, couplings(ig), biases(ig))) + ρ ./ sum(ρ) +end + +function brute_force(ig::IsingGraph; num_states::Int=1) + L = nv(ig) + if L == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end + sp = Spectrum(ig) + num_states = min(num_states, prod(rank_vec(ig))) + idx = partialsortperm(vec(sp.energies), 1:num_states) + Spectrum(sp.energies[idx], sp.states[idx]) +end + +function full_spectrum(ig::IsingGraph; num_states::Int=1) + if nv(ig) == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end + ig_rank = rank_vec(ig) + num_states = min(num_states, prod(ig_rank)) + σ = collect.(all_states(ig_rank)) + energies = energy(σ, couplings(ig), biases(ig)) + Spectrum(energies[begin:num_states], σ[begin:num_states]) end function inter_cluster_energy(cl1_states, J::Matrix, cl2_states) diff --git a/test/factor.jl b/test/factor.jl index e57c4ef..b32ab20 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -203,7 +203,7 @@ function create_example_factor_graph() ) end -const fg_state_to_spin = [ +fg_state_to_spin = [ ([1, 1], [-1, -1]), ([1, 2], [-1, 1]), ([2, 1], [1, -1]), ([2, 2], [1, 1]) ] diff --git a/test/ising.jl b/test/ising.jl index 96a88c7..0c4f2ce 100644 --- a/test/ising.jl +++ b/test/ising.jl @@ -175,7 +175,7 @@ end @test sum(R) ≈ 1 @test sum(ρ) ≈ 1 - @test [ ρ[idx.(σ)...] for σ ∈ sp.states ] ≈ R + @test [ρ[idx.(σ)...] for σ ∈ sp.states] ≈ R end @testset "Naive brute force for general spins" begin @@ -188,7 +188,7 @@ end rank = get_prop(ig, :rank) all = prod(rank) - sp = brute_force(ig, num_states=all) + sp = full_spectrum(ig, num_states=all) β = rand(Float64) ρ = exp.(-β .* sp.energies) @@ -196,7 +196,7 @@ end ϱ = ρ ./ sum(ρ) ϱ̃ = gibbs_tensor(ig, β) - @test [ ϱ̃[idx.(σ)...] for σ ∈ sp.states ] ≈ ϱ + @test [ϱ̃[idx.(σ)...] for σ ∈ sp.states] ≈ ϱ end @testset "Reading from Dict" begin @@ -250,7 +250,12 @@ end push!(cedges, (5, 6) => [(13, 16), (13, 18)]) push!(cedges, (6, 10) => [(18, 28)]) - push!(cedges, (10, 11) => [(28, 31), (28, 32), (28, 33), (29, 31), (29, 32), (29, 33), (30, 31), (30, 32), (30, 33)]) + push!( + cedges, + (10, 11) => [(28, 31), (28, 32), (28, 33), (29, 31), (29, 32), + (29, 33),(30, 31), (30, 32), (30, 33) + ] + ) push!(cedges, (2, 2) => [(4, 5), (4, 6), (5, 6), (6, 6)]) push!(cedges, (3, 3) => [(7, 8), (7, 9)]) diff --git a/test/runtests.jl b/test/runtests.jl index bd783a3..a152a6e 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -7,6 +7,11 @@ using Test Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) +idx(σ::Int) = (σ == -1) ? 1 : σ + 1 +energy(σ::Vector, J::Matrix, η::Vector=σ) = dot(σ, J, η) +energy(σ::Vector, h::Vector) = dot(h, σ) +energy(σ::Vector, ig::IsingGraph) = energy(σ, couplings(ig)) + energy(σ, biases(ig)) + my_tests = ["ising.jl", "factor.jl"] for my_test ∈ my_tests From ab2c9dbc971c7ac2e8a9caa15835c98f0114d464 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sat, 4 Dec 2021 17:48:50 +0100 Subject: [PATCH 021/218] clean up --- src/spectrum.jl | 32 -------------------------------- 1 file changed, 32 deletions(-) diff --git a/src/spectrum.jl b/src/spectrum.jl index fa94ea9..c123ebf 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -25,38 +25,6 @@ function Spectrum(ig::IsingGraph) Spectrum(energies, states) end -#= -function _kernel( - energies, states, J, h -) - L = size(J, 1) - - i = (blockIdx().x - 1) * blockDim().x + threadIdx().x - σ = 2 .* digits(i, base=2, pad=L) .- 1 - @inbounds energies[i] = dot(σ, J, σ) + dot(h, σ) - @inbounds states[i] = σ - nothing -end - -function CUDASpectrum(ig::IsingGraph) - L = nv(ig) - N = 2^L - - en_d = CUDA.zeros(Float64, N) - st_d = CUDA.Vector{Vector{Int}}(undef, N) - J_d, h_d = CUDA.zeros(L, L), CUDA.zeros(L) - - copyto!(couplings(ig), J_d) - copyto!(biases(ig), h_d) - - nb = ceil(Int, N/256) - CUDA.@sync begin - @cuda threads=N blocks=nb _kernel(en_d, st_d, J_d, h_d) - end - Spectrum(Array(en_d), Array(st_d)) -end -=# - function energy( σ::AbstractArray{Vector{Int}}, J::Matrix{<:Real}, h::Vector{<:Real} ) From fc028fe81a1a652ddac10edd41c6917dd5ca56a4 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sat, 4 Dec 2021 18:51:01 +0100 Subject: [PATCH 022/218] clean up --- benchmarks/spectrum.jl | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 358748c..3dcf941 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -8,7 +8,8 @@ function bench(instance::String) ig = ising_graph(instance) cl = split_into_clusters(ig, super_square_lattice((m, n, t))) - @time sp = brute_force(cl[1, 1], num_states=100) + @time brute_force(cl[1, 1], num_states=100) + nothing end bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); From 838fef55735cdfca7476f5685e5f4bfa3aaf3bbc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=C5=81ukasz=20Pawela?= Date: Sat, 4 Dec 2021 22:55:05 +0100 Subject: [PATCH 023/218] add rudementary gpu brute force --- benchmarks/spectrum.jl | 51 +++++++++++++++++++++++++++++++++++++++--- 1 file changed, 48 insertions(+), 3 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 3dcf941..d3061bc 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -1,6 +1,6 @@ -using SpinGlassNetworks - +using SpinGlassNetworks, LightGraphs +using CUDA, LinearAlgebra function bench(instance::String) m = 2 n = 2 @@ -12,4 +12,49 @@ function bench(instance::String) nothing end -bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +function kernel(J, energies, σ) + L = size(J, 1) + + i = blockIdx().x + j = threadIdx().x + + s = (i - 1) * blockDim().x + j + s1 = copy(s) + for k=1:L + @inbounds σ[k, s] = s1%2 + s1 = div(s1, 2) + end + for k=1:L + @inbounds energies[s] += J[k, k] * σ[k, s] + for l=(k+1):L + @inbounds energies[s] += J[k, l] * σ[k, s] * σ[l, s] + end + end + + return +end + +function bench2(instance::String) + m = 2 + n = 2 + t = 24 + + ig = ising_graph(instance) + cl = split_into_clusters(ig, super_square_lattice((m, n, t))) + J = couplings(cl[1, 1]) + Diagonal(biases(cl[1, 1])) + L = nv(cl[1, 1]) + N = 2^L + @time begin + energies = CUDA.zeros(N) + σ = CUDA.zeros(L, N) + J_dev = CUDA.CuArray(J) + @cuda threads=1024 blocks=(2^(L-10)) kernel(J_dev, energies, σ) + energies_cpu = Array(energies) + end + # @time @cuda threads=1024 blocks=4 kernel(J, energies) + nothing +end + +# bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); From d4f3bc09c3ae7dc9b8be9a388515261c00c73db5 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sat, 4 Dec 2021 22:59:42 +0100 Subject: [PATCH 024/218] clen up --- src/SpinGlassNetworks.jl | 1 + src/spectrum.jl | 39 +++++++++++++++++++++++++++++++++++++++ 2 files changed, 40 insertions(+) diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 9b53166..c44ad9a 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -6,6 +6,7 @@ module SpinGlassNetworks using DocStringExtensions using LinearAlgebra using Base.Cartesian + using CUDA import Base.Prehashed diff --git a/src/spectrum.jl b/src/spectrum.jl index c123ebf..d7e66a6 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -9,6 +9,45 @@ struct Spectrum states::Vector{Vector{Int}} end +#= +function _kernel( + energies, states, J, h +) + L = size(J, 1) + + σ = CUDA.zeros(Int, L) + for i = 1:L σ[i] = -1 end + + en = 0.0 + for i = 1:L + en += h[i] #σ[i] * h[i] + for j = 1:L en += J[i, j] end #σ[i] * J[i, j] * σ[j] end + end + + idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x + energies[idx] = en + states[idx] = σ + return +end + +function CUDASpectrum(ig::IsingGraph) + L = nv(ig) + N = 2^L + + en = CUDA.zeros(Float64, N) + st = CUDA.Vector{Vector{Int}}(undef, N) + J = CUDA.zeros(L, L) + h = CUDA.zeros(L) + + copyto!(couplings(ig), J) + copyto!(biases(ig), h) + + nb = ceil(Int, N / 256) + @cuda threads=N blocks=nb _kernel(en, st, J, h) + Spectrum(Array(en), Array(st)) +end +=# + function Spectrum(ig::IsingGraph) L = nv(ig) N = 2^L From 30ab0771c4e170922f73e8f07679ab056a727b19 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sat, 4 Dec 2021 23:01:48 +0100 Subject: [PATCH 025/218] rm commented functions --- src/spectrum.jl | 39 --------------------------------------- 1 file changed, 39 deletions(-) diff --git a/src/spectrum.jl b/src/spectrum.jl index d7e66a6..c123ebf 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -9,45 +9,6 @@ struct Spectrum states::Vector{Vector{Int}} end -#= -function _kernel( - energies, states, J, h -) - L = size(J, 1) - - σ = CUDA.zeros(Int, L) - for i = 1:L σ[i] = -1 end - - en = 0.0 - for i = 1:L - en += h[i] #σ[i] * h[i] - for j = 1:L en += J[i, j] end #σ[i] * J[i, j] * σ[j] end - end - - idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x - energies[idx] = en - states[idx] = σ - return -end - -function CUDASpectrum(ig::IsingGraph) - L = nv(ig) - N = 2^L - - en = CUDA.zeros(Float64, N) - st = CUDA.Vector{Vector{Int}}(undef, N) - J = CUDA.zeros(L, L) - h = CUDA.zeros(L) - - copyto!(couplings(ig), J) - copyto!(biases(ig), h) - - nb = ceil(Int, N / 256) - @cuda threads=N blocks=nb _kernel(en, st, J, h) - Spectrum(Array(en), Array(st)) -end -=# - function Spectrum(ig::IsingGraph) L = nv(ig) N = 2^L From 73d38e9be8d04996878a2da0377a667bc98920bf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=C5=81ukasz=20Pawela?= Date: Sat, 4 Dec 2021 23:32:42 +0100 Subject: [PATCH 026/218] fix binary conversion --- benchmarks/spectrum.jl | 3 +++ 1 file changed, 3 insertions(+) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index d3061bc..37d247d 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -22,6 +22,9 @@ function kernel(J, energies, σ) s1 = copy(s) for k=1:L @inbounds σ[k, s] = s1%2 + if s1 == 1 + break + end s1 = div(s1, 2) end for k=1:L From 2b9498724641d1fa02687ee87235d6feecd7c8f4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=C5=81ukasz=20Pawela?= Date: Sun, 5 Dec 2021 00:08:09 +0100 Subject: [PATCH 027/218] add sortperm (requires cuda from master) --- benchmarks/spectrum.jl | 2 ++ 1 file changed, 2 insertions(+) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 37d247d..b9baf80 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -53,6 +53,8 @@ function bench2(instance::String) J_dev = CUDA.CuArray(J) @cuda threads=1024 blocks=(2^(L-10)) kernel(J_dev, energies, σ) energies_cpu = Array(energies) + # perm = sortperm(energies_cpu) + sortperm(energies) end # @time @cuda threads=1024 blocks=4 kernel(J, energies) nothing From 370f370d512e32eac626235de97f1830904c542f Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 00:26:47 +0100 Subject: [PATCH 028/218] compare energies --- benchmarks/spectrum.jl | 20 ++++++++++++-------- src/SpinGlassNetworks.jl | 1 - 2 files changed, 12 insertions(+), 9 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index d3061bc..a0b9202 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -1,6 +1,7 @@ using SpinGlassNetworks, LightGraphs using CUDA, LinearAlgebra + function bench(instance::String) m = 2 n = 2 @@ -8,8 +9,8 @@ function bench(instance::String) ig = ising_graph(instance) cl = split_into_clusters(ig, super_square_lattice((m, n, t))) - @time brute_force(cl[1, 1], num_states=100) - nothing + @time sp = brute_force(cl[1, 1], num_states=100) + sp end function kernel(J, energies, σ) @@ -19,18 +20,19 @@ function kernel(J, energies, σ) j = threadIdx().x s = (i - 1) * blockDim().x + j - s1 = copy(s) + s1 = copy(s) for k=1:L @inbounds σ[k, s] = s1%2 s1 = div(s1, 2) end + for k=1:L @inbounds energies[s] += J[k, k] * σ[k, s] for l=(k+1):L @inbounds energies[s] += J[k, l] * σ[k, s] * σ[l, s] end end - + return end @@ -52,9 +54,11 @@ function bench2(instance::String) energies_cpu = Array(energies) end # @time @cuda threads=1024 blocks=4 kernel(J, energies) - nothing + energies_cpu end -# bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +en = bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +#bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); + +minimum(sp.energies) ≈ minimum(sort(en)) diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index c44ad9a..9b53166 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -6,7 +6,6 @@ module SpinGlassNetworks using DocStringExtensions using LinearAlgebra using Base.Cartesian - using CUDA import Base.Prehashed From fc8a82a9506ec025976062e76a6feadaf231bc04 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 10:40:33 +0100 Subject: [PATCH 029/218] add my_digits --- benchmarks/spectrum.jl | 19 +++++++++++++++++-- 1 file changed, 17 insertions(+), 2 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 4b2596f..84bb8c1 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -1,6 +1,7 @@ using SpinGlassNetworks, LightGraphs using CUDA, LinearAlgebra +using Bits function bench(instance::String) m = 2 @@ -13,6 +14,12 @@ function bench(instance::String) sp end +function my_digits(d::Int, L::Int) + σ = zeros(Int, L) + for i=1:L if tstbit(d, i) @inbounds σ[k] = 1 end end + σ +end + function kernel(J, energies, σ) L = size(J, 1) @@ -47,6 +54,8 @@ function bench2(instance::String) ig = ising_graph(instance) cl = split_into_clusters(ig, super_square_lattice((m, n, t))) J = couplings(cl[1, 1]) + Diagonal(biases(cl[1, 1])) + + L = nv(cl[1, 1]) N = 2^L @time begin @@ -63,7 +72,13 @@ function bench2(instance::String) end sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -en = bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +#en = bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); #bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -minimum(sp.energies) ≈ minimum(sort(en)) +#minimum(sp.energies) ≈ minimum(sort(en)) + +i=9 +L=15 + +println(my_digits(i, L)) +println(digits(i, base=2, pad=L)) From 9d6e9d2772ac17893365144c70bd3a9aa73daaab Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 11:03:15 +0100 Subject: [PATCH 030/218] add new kernel (still does not work, but close) --- benchmarks/spectrum.jl | 42 +++++++++++++++++++++++++++++++++++++++++- 1 file changed, 41 insertions(+), 1 deletion(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 84bb8c1..c9c5a01 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -20,6 +20,45 @@ function my_digits(d::Int, L::Int) σ end +function bg_kernel(J, energies, σ) + s = (blockIdx().x - 1) * blockDim().x + threadIdx().x + L = size(J, 1) + + for i=1:L if tstbit(L, i) @inbounds σ[i] = 1 end end + + en = 0.0 + for k=1:L + en += J[k, k] * σ[k] + for l=(k+1):L en += σ[k] * J[k, l] * σ[l] end + end + @inbounds energies[s] = en + return +end + +function bench3(instance::String) + m = 2 + n = 2 + t = 24 + + ig = ising_graph(instance) + cl = split_into_clusters(ig, super_square_lattice((m, n, t))) + J = couplings(cl[1, 1]) + Diagonal(biases(cl[1, 1])) + + L = nv(cl[1, 1]) + N = 2^L + @time begin + energies = CUDA.zeros(N) + σ = CUDA.zeros(L) + J_dev = CUDA.CuArray(J) + @cuda threads=1024 blocks=(2^(L-10)) bg_kernel(J_dev, energies, σ) + energies_cpu = Array(energies) + # perm = sortperm(energies_cpu) + sortperm(energies) + end + # @time @cuda threads=1024 blocks=4 kernel(J, energies) + energies_cpu +end + function kernel(J, energies, σ) L = size(J, 1) @@ -28,6 +67,7 @@ function kernel(J, energies, σ) s = (i - 1) * blockDim().x + j s1 = copy(s) + for k=1:L @inbounds σ[k, s] = s1%2 if s1 == 1 @@ -72,7 +112,7 @@ function bench2(instance::String) end sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -#en = bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +en = bench3("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); #bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); #minimum(sp.energies) ≈ minimum(sort(en)) From 9291cc39f54589f88542ccbac710925caf37773f Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 11:20:22 +0100 Subject: [PATCH 031/218] something works --- benchmarks/spectrum.jl | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index c9c5a01..1521133 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -16,22 +16,20 @@ end function my_digits(d::Int, L::Int) σ = zeros(Int, L) - for i=1:L if tstbit(d, i) @inbounds σ[k] = 1 end end + for i=1:L if tstbit(d, i) @inbounds σ[1] = 1 end end σ end function bg_kernel(J, energies, σ) s = (blockIdx().x - 1) * blockDim().x + threadIdx().x - L = size(J, 1) + L = size(σ, 1) for i=1:L if tstbit(L, i) @inbounds σ[i] = 1 end end - en = 0.0 for k=1:L - en += J[k, k] * σ[k] - for l=(k+1):L en += σ[k] * J[k, l] * σ[l] end + @inbounds energies[s] += J[k, k] * σ[k] + for l=(k+1):L @inbounds energies[s] += σ[k] * J[k, l] * σ[l] end end - @inbounds energies[s] = en return end @@ -53,7 +51,7 @@ function bench3(instance::String) @cuda threads=1024 blocks=(2^(L-10)) bg_kernel(J_dev, energies, σ) energies_cpu = Array(energies) # perm = sortperm(energies_cpu) - sortperm(energies) + #sortperm(energies) end # @time @cuda threads=1024 blocks=4 kernel(J, energies) energies_cpu From fc8eb28cdac64a98b80028eadb07e56f265ed8c3 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 11:36:46 +0100 Subject: [PATCH 032/218] fix bits --- benchmarks/spectrum.jl | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 1521133..482b002 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -16,7 +16,7 @@ end function my_digits(d::Int, L::Int) σ = zeros(Int, L) - for i=1:L if tstbit(d, i) @inbounds σ[1] = 1 end end + for i=1:L if tstbit(d, i) @inbounds σ[i] = 1 end end σ end @@ -115,8 +115,8 @@ en = bench3("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); #minimum(sp.energies) ≈ minimum(sort(en)) -i=9 -L=15 +println(minimum(sp.energies)) +println(minimum(sort(en))) -println(my_digits(i, L)) -println(digits(i, base=2, pad=L)) +L=100 +@assert all(my_digits(i, L) == digits(i, base=2, pad=L) for i=1:L) From 510840ed8f58ff2919bff322e67284bf0f08a6ef Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 12:05:46 +0100 Subject: [PATCH 033/218] should work but it does not --- benchmarks/spectrum.jl | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 482b002..45ec84e 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -28,7 +28,7 @@ function bg_kernel(J, energies, σ) for k=1:L @inbounds energies[s] += J[k, k] * σ[k] - for l=(k+1):L @inbounds energies[s] += σ[k] * J[k, l] * σ[l] end + for l=(k+1):L @inbounds energies[s] += σ[k] * J[l, k] * σ[l] end end return end @@ -57,6 +57,7 @@ function bench3(instance::String) energies_cpu end +#= function kernel(J, energies, σ) L = size(J, 1) @@ -108,6 +109,7 @@ function bench2(instance::String) # @time @cuda threads=1024 blocks=4 kernel(J, energies) energies_cpu end +=# sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); en = bench3("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); From c6c5c476becb30210ba4d08bfcc2d5df35b32c21 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 12:08:53 +0100 Subject: [PATCH 034/218] gnoj --- benchmarks/spectrum.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 45ec84e..35c17e7 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -28,7 +28,7 @@ function bg_kernel(J, energies, σ) for k=1:L @inbounds energies[s] += J[k, k] * σ[k] - for l=(k+1):L @inbounds energies[s] += σ[k] * J[l, k] * σ[l] end + for l=1:L @inbounds energies[s] += σ[k] * J[l, k] * σ[l] end # 1 -> (k+1) end return end From 9e4c86bf4b35b87bfa910f6596ca1ab50a57fc04 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 12:41:33 +0100 Subject: [PATCH 035/218] fix indexing --- benchmarks/spectrum.jl | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 35c17e7..2a8c68b 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -20,15 +20,15 @@ function my_digits(d::Int, L::Int) σ end -function bg_kernel(J, energies, σ) - s = (blockIdx().x - 1) * blockDim().x + threadIdx().x +function kernel(J, energies, σ) + idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x L = size(σ, 1) - for i=1:L if tstbit(L, i) @inbounds σ[i] = 1 end end + for i=1:L if tstbit(idx, i) @inbounds σ[i] = 1 end end for k=1:L - @inbounds energies[s] += J[k, k] * σ[k] - for l=1:L @inbounds energies[s] += σ[k] * J[l, k] * σ[l] end # 1 -> (k+1) + @inbounds energies[idx] += J[k, k] * σ[k] + for l=1:L @inbounds energies[idx] += σ[k] * J[k, l] * σ[l] end # 1 -> (k+1) end return end @@ -48,8 +48,10 @@ function bench3(instance::String) energies = CUDA.zeros(N) σ = CUDA.zeros(L) J_dev = CUDA.CuArray(J) - @cuda threads=1024 blocks=(2^(L-10)) bg_kernel(J_dev, energies, σ) + @cuda threads=1024 blocks=(2^(L-10)) kernel(J_dev, energies, σ) energies_cpu = Array(energies) + σ_cpu = Array(σ) + println(σ[1:5]) # perm = sortperm(energies_cpu) #sortperm(energies) end @@ -115,10 +117,11 @@ sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); en = bench3("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); #bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -#minimum(sp.energies) ≈ minimum(sort(en)) +#minimum(sp.energies) ≈ minimum(en) println(minimum(sp.energies)) -println(minimum(sort(en))) +println(en[1:10]) + L=100 @assert all(my_digits(i, L) == digits(i, base=2, pad=L) for i=1:L) From 7b063650c4bd14a71719e81711001294dc5c3813 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 12:50:14 +0100 Subject: [PATCH 036/218] improve stuff a bit but still :( --- benchmarks/spectrum.jl | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 2a8c68b..74ed126 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -24,11 +24,11 @@ function kernel(J, energies, σ) idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x L = size(σ, 1) - for i=1:L if tstbit(idx, i) @inbounds σ[i] = 1 end end + for i=1:L if tstbit(idx, i) @inbounds σ[i, idx] = 1 end end for k=1:L - @inbounds energies[idx] += J[k, k] * σ[k] - for l=1:L @inbounds energies[idx] += σ[k] * J[k, l] * σ[l] end # 1 -> (k+1) + @inbounds energies[idx] += J[k, k] * σ[k, idx] + for l=1:L @inbounds energies[idx] += σ[k, idx] * J[k, l] * σ[l, idx] end # 1 -> (k+1) end return end @@ -46,12 +46,11 @@ function bench3(instance::String) N = 2^L @time begin energies = CUDA.zeros(N) - σ = CUDA.zeros(L) + σ = CUDA.zeros(Int, L, N) J_dev = CUDA.CuArray(J) @cuda threads=1024 blocks=(2^(L-10)) kernel(J_dev, energies, σ) energies_cpu = Array(energies) σ_cpu = Array(σ) - println(σ[1:5]) # perm = sortperm(energies_cpu) #sortperm(energies) end @@ -117,10 +116,10 @@ sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); en = bench3("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); #bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -#minimum(sp.energies) ≈ minimum(en) +#minimum(sp.energies) ≈ println(minimum(sp.energies)) -println(en[1:10]) +println(minimum(en)) L=100 From 041ef76f5fcb3105c694bd55305c319fb84100bf Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 13:13:28 +0100 Subject: [PATCH 037/218] almost there --- benchmarks/spectrum.jl | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 74ed126..67e5522 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -46,7 +46,7 @@ function bench3(instance::String) N = 2^L @time begin energies = CUDA.zeros(N) - σ = CUDA.zeros(Int, L, N) + σ = CUDA.zeros(Int, L, N) .- 1 J_dev = CUDA.CuArray(J) @cuda threads=1024 blocks=(2^(L-10)) kernel(J_dev, energies, σ) energies_cpu = Array(energies) @@ -116,8 +116,6 @@ sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); en = bench3("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); #bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -#minimum(sp.energies) ≈ - println(minimum(sp.energies)) println(minimum(en)) From 405af9e0ae5439a695458538066c27c6112e6042 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 13:31:10 +0100 Subject: [PATCH 038/218] fix issues with Spectrum --- benchmarks/spectrum.jl | 85 ++++++------------------------------------ src/spectrum.jl | 2 +- 2 files changed, 12 insertions(+), 75 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 67e5522..9dc41e9 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -3,23 +3,17 @@ using SpinGlassNetworks, LightGraphs using CUDA, LinearAlgebra using Bits -function bench(instance::String) +function bench_cpu(instance::String, max_states::Int=100) m = 2 n = 2 t = 24 ig = ising_graph(instance) cl = split_into_clusters(ig, super_square_lattice((m, n, t))) - @time sp = brute_force(cl[1, 1], num_states=100) + @time sp = brute_force(cl[1, 1], num_states=max_states) sp end -function my_digits(d::Int, L::Int) - σ = zeros(Int, L) - for i=1:L if tstbit(d, i) @inbounds σ[i] = 1 end end - σ -end - function kernel(J, energies, σ) idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x L = size(σ, 1) @@ -33,7 +27,7 @@ function kernel(J, energies, σ) return end -function bench3(instance::String) +function bench_gpu(instance::String, max_states::Int=100) m = 2 n = 2 t = 24 @@ -49,76 +43,19 @@ function bench3(instance::String) σ = CUDA.zeros(Int, L, N) .- 1 J_dev = CUDA.CuArray(J) @cuda threads=1024 blocks=(2^(L-10)) kernel(J_dev, energies, σ) - energies_cpu = Array(energies) - σ_cpu = Array(σ) - # perm = sortperm(energies_cpu) #sortperm(energies) - end - # @time @cuda threads=1024 blocks=4 kernel(J, energies) - energies_cpu -end - -#= -function kernel(J, energies, σ) - L = size(J, 1) - - i = blockIdx().x - j = threadIdx().x - - s = (i - 1) * blockDim().x + j - s1 = copy(s) - - for k=1:L - @inbounds σ[k, s] = s1%2 - if s1 == 1 - break - end - s1 = div(s1, 2) - end - - for k=1:L - @inbounds energies[s] += J[k, k] * σ[k, s] - for l=(k+1):L - @inbounds energies[s] += J[k, l] * σ[k, s] * σ[l, s] - end - end - - return -end - -function bench2(instance::String) - m = 2 - n = 2 - t = 24 - - ig = ising_graph(instance) - cl = split_into_clusters(ig, super_square_lattice((m, n, t))) - J = couplings(cl[1, 1]) + Diagonal(biases(cl[1, 1])) - - - L = nv(cl[1, 1]) - N = 2^L - @time begin - energies = CUDA.zeros(N) - σ = CUDA.zeros(L, N) - J_dev = CUDA.CuArray(J) - @cuda threads=1024 blocks=(2^(L-10)) kernel(J_dev, energies, σ) energies_cpu = Array(energies) - # perm = sortperm(energies_cpu) - sortperm(energies) + σ_cpu = Array(σ) + perm = partialsortperm(energies_cpu, 1:max_states) end - # @time @cuda threads=1024 blocks=4 kernel(J, energies) - energies_cpu + Spectrum(energies_cpu[perm], σ_cpu[:, perm]) end -=# -sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -en = bench3("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -#bench2("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -println(minimum(sp.energies)) -println(minimum(en)) +sp_cpu = bench_cpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +sp_gpu = bench_gpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +sp_cpu.energies ≈ sp_gpu.energies -L=100 -@assert all(my_digits(i, L) == digits(i, base=2, pad=L) for i=1:L) +println(minimum(sp_gpu.energies)) +println(minimum(sp_cpu.energies)) diff --git a/src/spectrum.jl b/src/spectrum.jl index c123ebf..19980cc 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -6,7 +6,7 @@ all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank).. struct Spectrum energies::Vector{Float64} - states::Vector{Vector{Int}} + states::Union{Vector{Vector{Int}}, Matrix{Int}} end function Spectrum(ig::IsingGraph) From df6c0d432a46fec47e562ed542f1f0361d59d297 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 13:44:03 +0100 Subject: [PATCH 039/218] works --- benchmarks/spectrum.jl | 2 ++ 1 file changed, 2 insertions(+) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 9dc41e9..4dc1d7b 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -59,3 +59,5 @@ sp_cpu.energies ≈ sp_gpu.energies println(minimum(sp_gpu.energies)) println(minimum(sp_cpu.energies)) + +sp_gpu.states[:, begin] == sp_cpu.states[begin] From c842f2841bd0799c08e2b3e2ca6cc424cea471e8 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 14:45:17 +0100 Subject: [PATCH 040/218] check all states --- benchmarks/spectrum.jl | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 4dc1d7b..4459574 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -60,4 +60,7 @@ sp_cpu.energies ≈ sp_gpu.energies println(minimum(sp_gpu.energies)) println(minimum(sp_cpu.energies)) -sp_gpu.states[:, begin] == sp_cpu.states[begin] +@assert all( + sp_gpu.states[:, i] == sp_cpu.states[i] + for i ∈ 1:size(sp_cpu.states, 1) +) From 47787d019d4f005bc022ff3dca572cfb27d5b203 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 15:04:38 +0100 Subject: [PATCH 041/218] all work --- benchmarks/spectrum.jl | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 4459574..aadfcdd 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -22,7 +22,7 @@ function kernel(J, energies, σ) for k=1:L @inbounds energies[idx] += J[k, k] * σ[k, idx] - for l=1:L @inbounds energies[idx] += σ[k, idx] * J[k, l] * σ[l, idx] end # 1 -> (k+1) + for l=k+1:L @inbounds energies[idx] += σ[k, idx] * J[k, l] * σ[l, idx] end end return end @@ -51,15 +51,10 @@ function bench_gpu(instance::String, max_states::Int=100) Spectrum(energies_cpu[perm], σ_cpu[:, perm]) end - sp_cpu = bench_cpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); sp_gpu = bench_gpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -sp_cpu.energies ≈ sp_gpu.energies - -println(minimum(sp_gpu.energies)) -println(minimum(sp_cpu.energies)) - +@assert sp_gpu.energies ≈ sp_cpu.energies @assert all( sp_gpu.states[:, i] == sp_cpu.states[i] for i ∈ 1:size(sp_cpu.states, 1) From 0d7b5c13edde29511ce7e45cbd9b7090badad439 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 15:05:16 +0100 Subject: [PATCH 042/218] clean up --- benchmarks/spectrum.jl | 1 - 1 file changed, 1 deletion(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index aadfcdd..e45b1f2 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -43,7 +43,6 @@ function bench_gpu(instance::String, max_states::Int=100) σ = CUDA.zeros(Int, L, N) .- 1 J_dev = CUDA.CuArray(J) @cuda threads=1024 blocks=(2^(L-10)) kernel(J_dev, energies, σ) - #sortperm(energies) energies_cpu = Array(energies) σ_cpu = Array(σ) perm = partialsortperm(energies_cpu, 1:max_states) From 0d64212354be85983b85733fd61b2303841dee3b Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 15:10:42 +0100 Subject: [PATCH 043/218] add more control over CUDA lauch --- benchmarks/spectrum.jl | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index e45b1f2..8312b51 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -38,11 +38,12 @@ function bench_gpu(instance::String, max_states::Int=100) L = nv(cl[1, 1]) N = 2^L + k = 10 @time begin energies = CUDA.zeros(N) σ = CUDA.zeros(Int, L, N) .- 1 J_dev = CUDA.CuArray(J) - @cuda threads=1024 blocks=(2^(L-10)) kernel(J_dev, energies, σ) + @cuda threads=2^k blocks=(2^(L-k)) kernel(J_dev, energies, σ) energies_cpu = Array(energies) σ_cpu = Array(σ) perm = partialsortperm(energies_cpu, 1:max_states) From 5ebfd6adbddf30d719b794220345f1e581adb188 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Sun, 5 Dec 2021 16:31:06 +0100 Subject: [PATCH 044/218] all tests pass --- benchmarks/spectrum.jl | 5 ++--- src/spectrum.jl | 2 +- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 8312b51..589344d 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -24,7 +24,6 @@ function kernel(J, energies, σ) @inbounds energies[idx] += J[k, k] * σ[k, idx] for l=k+1:L @inbounds energies[idx] += σ[k, idx] * J[k, l] * σ[l, idx] end end - return end function bench_gpu(instance::String, max_states::Int=100) @@ -48,7 +47,7 @@ function bench_gpu(instance::String, max_states::Int=100) σ_cpu = Array(σ) perm = partialsortperm(energies_cpu, 1:max_states) end - Spectrum(energies_cpu[perm], σ_cpu[:, perm]) + Spectrum(energies_cpu[perm], [σ_cpu[:, i] for i ∈ 1:size(σ_cpu, 2)][perm]) end sp_cpu = bench_cpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); @@ -56,6 +55,6 @@ sp_gpu = bench_gpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); @assert sp_gpu.energies ≈ sp_cpu.energies @assert all( - sp_gpu.states[:, i] == sp_cpu.states[i] + sp_gpu.states[i] == sp_cpu.states[i] for i ∈ 1:size(sp_cpu.states, 1) ) diff --git a/src/spectrum.jl b/src/spectrum.jl index 19980cc..73876a5 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -6,7 +6,7 @@ all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank).. struct Spectrum energies::Vector{Float64} - states::Union{Vector{Vector{Int}}, Matrix{Int}} + states::Vector{Vector{Int}} #Union{Vector{Vector{Int}}, Matrix{Int}} end function Spectrum(ig::IsingGraph) From 0836080210254215d083af8a6db8df065ec61521 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=C5=81ukasz=20Pawela?= Date: Mon, 6 Dec 2021 21:27:40 +0100 Subject: [PATCH 045/218] add specializiation for brute_force devices --- src/spectrum.jl | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/spectrum.jl b/src/spectrum.jl index 73876a5..8d25e89 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -37,7 +37,9 @@ function gibbs_tensor(ig::IsingGraph, β::Real=1.0) ρ ./ sum(ρ) end -function brute_force(ig::IsingGraph; num_states::Int=1) +brute_force(ig::IsingGraph, s::Symbol=:CPU; num_states::Int=1) = brute_force(ig, Val(s); num_states) + +function brute_force(ig::IsingGraph, ::Val{:CPU}; num_states::Int=1) L = nv(ig) if L == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end sp = Spectrum(ig) From 47e9c224e6279db8adad03431e2aa87e2e9dbc9f Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 7 Dec 2021 00:06:35 +0100 Subject: [PATCH 046/218] clean up --- src/spectrum.jl | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/spectrum.jl b/src/spectrum.jl index 8d25e89..51fdf78 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -37,7 +37,9 @@ function gibbs_tensor(ig::IsingGraph, β::Real=1.0) ρ ./ sum(ρ) end -brute_force(ig::IsingGraph, s::Symbol=:CPU; num_states::Int=1) = brute_force(ig, Val(s); num_states) +function brute_force(ig::IsingGraph, s::Symbol=:CPU; num_states::Int=1) + brute_force(ig, Val(s); num_states) +end function brute_force(ig::IsingGraph, ::Val{:CPU}; num_states::Int=1) L = nv(ig) From cd3fab9b2c8fc1b49b934504748435699a42bbda Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 7 Dec 2021 12:49:56 +0100 Subject: [PATCH 047/218] clean up --- benchmarks/spectrum.jl | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 589344d..c80a2b2 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -54,7 +54,4 @@ sp_cpu = bench_cpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); sp_gpu = bench_gpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); @assert sp_gpu.energies ≈ sp_cpu.energies -@assert all( - sp_gpu.states[i] == sp_cpu.states[i] - for i ∈ 1:size(sp_cpu.states, 1) -) +@assert sp_gpu.states == sp_cpu.states From e8b12a2152d2cf64d9c0ac0ab3f07d4e0ea2c6aa Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 7 Dec 2021 17:52:33 +0100 Subject: [PATCH 048/218] clean up energy mess --- benchmarks/spectrum.jl | 50 +++-------------------------- src/spectrum.jl | 37 ++++++++++++---------- test/factor.jl | 2 +- test/ising.jl | 71 +++++++++++------------------------------- test/runtests.jl | 5 --- 5 files changed, 44 insertions(+), 121 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index c80a2b2..3da6083 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -1,57 +1,17 @@ -using SpinGlassNetworks, LightGraphs -using CUDA, LinearAlgebra -using Bits +using SpinGlassNetworks -function bench_cpu(instance::String, max_states::Int=100) +function bench(instance::String, max_states::Int=100) m = 2 n = 2 t = 24 + println("Threads: ", Threads.nthreads()) + ig = ising_graph(instance) cl = split_into_clusters(ig, super_square_lattice((m, n, t))) @time sp = brute_force(cl[1, 1], num_states=max_states) sp end -function kernel(J, energies, σ) - idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x - L = size(σ, 1) - - for i=1:L if tstbit(idx, i) @inbounds σ[i, idx] = 1 end end - - for k=1:L - @inbounds energies[idx] += J[k, k] * σ[k, idx] - for l=k+1:L @inbounds energies[idx] += σ[k, idx] * J[k, l] * σ[l, idx] end - end -end - -function bench_gpu(instance::String, max_states::Int=100) - m = 2 - n = 2 - t = 24 - - ig = ising_graph(instance) - cl = split_into_clusters(ig, super_square_lattice((m, n, t))) - J = couplings(cl[1, 1]) + Diagonal(biases(cl[1, 1])) - - L = nv(cl[1, 1]) - N = 2^L - k = 10 - @time begin - energies = CUDA.zeros(N) - σ = CUDA.zeros(Int, L, N) .- 1 - J_dev = CUDA.CuArray(J) - @cuda threads=2^k blocks=(2^(L-k)) kernel(J_dev, energies, σ) - energies_cpu = Array(energies) - σ_cpu = Array(σ) - perm = partialsortperm(energies_cpu, 1:max_states) - end - Spectrum(energies_cpu[perm], [σ_cpu[:, i] for i ∈ 1:size(σ_cpu, 2)][perm]) -end - -sp_cpu = bench_cpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); -sp_gpu = bench_gpu("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); - -@assert sp_gpu.energies ≈ sp_cpu.energies -@assert sp_gpu.states == sp_cpu.states +sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); diff --git a/src/spectrum.jl b/src/spectrum.jl index 51fdf78..35eacda 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -1,39 +1,38 @@ export all_states, local_basis, gibbs_tensor, brute_force export full_spectrum, Spectrum, idx, local_basis, energy -local_basis(d::Int) = union(-1, 1:d-1) +@inline idx(σ::Int) = (σ == -1) ? 1 : σ + 1 +@inline local_basis(d::Int) = union(-1, 1:d-1) all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank)...) +const State = Vector{Int} struct Spectrum - energies::Vector{Float64} - states::Vector{Vector{Int}} #Union{Vector{Vector{Int}}, Matrix{Int}} + energies::Vector{<:Real} + states::AbstractArray{State} +end + +energy(σ::State, ig::IsingGraph) = dot(σ, couplings(ig), σ) + dot(biases(ig), σ) +function energy(σ::AbstractArray{State}, ig::IsingGraph) + J = couplings(ig), h = biases(ig) + dot.(σ, Ref(J), σ) + dot.(Ref(h), σ) end function Spectrum(ig::IsingGraph) L = nv(ig) N = 2^L - energies = zeros(Float64, N) - states = Vector{Vector{Int}}(undef, N) - - J, h = couplings(ig), biases(ig) + states = Vector{State}(undef, N) Threads.@threads for i = 0:N-1 σ = 2 .* digits(i, base=2, pad=L) .- 1 - @inbounds energies[i+1] = dot(σ, J, σ) + dot(h, σ) + @inbounds energies[i+1] = energy(σ, ig) @inbounds states[i+1] = σ end Spectrum(energies, states) end -function energy( - σ::AbstractArray{Vector{Int}}, J::Matrix{<:Real}, h::Vector{<:Real} -) - dot.(σ, Ref(J), σ) + dot.(Ref(h), σ) -end - function gibbs_tensor(ig::IsingGraph, β::Real=1.0) σ = collect.(all_states(rank_vec(ig))) - ρ = exp.(-β .* energy(σ, couplings(ig), biases(ig))) + ρ = exp.(-β .* energy.(σ, Ref(ig))) ρ ./ sum(ρ) end @@ -55,10 +54,14 @@ function full_spectrum(ig::IsingGraph; num_states::Int=1) ig_rank = rank_vec(ig) num_states = min(num_states, prod(ig_rank)) σ = collect.(all_states(ig_rank)) - energies = energy(σ, couplings(ig), biases(ig)) + energies = energy.(σ, Ref(ig)) Spectrum(energies[begin:num_states], σ[begin:num_states]) end -function inter_cluster_energy(cl1_states, J::Matrix, cl2_states) +function inter_cluster_energy( + cl1_states::Vector{State}, + J::Matrix{<:Real}, + cl2_states::Vector{State} +) hcat(collect.(cl1_states)...)' * J * hcat(collect.(cl2_states)...) end diff --git a/test/factor.jl b/test/factor.jl index cdfe3f5..cfbb619 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -257,6 +257,6 @@ end for (k, v) ∈ d spins[k] = v end - @test factor_graph_energy(fg, state) ≈ energy(spins, ig) + @test factor_graph_energy(fg, state) ≈ energy(Int.(spins), ig) end end diff --git a/test/ising.jl b/test/ising.jl index 0c4f2ce..2cd7235 100644 --- a/test/ising.jl +++ b/test/ising.jl @@ -129,37 +129,26 @@ end end end - @testset "Ising" begin L = 4 N = L^2 instance = "$(@__DIR__)/instances/$(N)_001.txt" - ig = ising_graph(instance) @test nv(ig) == N - - for i ∈ 1:N - @test has_vertex(ig, i) - end + for i ∈ 1:N @test has_vertex(ig, i) end A = adjacency_matrix(ig) - B = zeros(Int, N, N) for i ∈ 1:N nbrs = SpinGlassNetworks.unique_neighbors(ig, i) - for j ∈ nbrs - B[i, j] = 1 - end + for j ∈ nbrs B[i, j] = 1 end end - @test B + B' == A @testset "Naive brute force for +/-1" begin k = 2^N - sp = brute_force(ig, num_states=k) - s = 5 @test sp.energies ≈ energy.(sp.states, Ref(ig)) @@ -181,10 +170,9 @@ end @testset "Naive brute force for general spins" begin L = 4 instance = "$(@__DIR__)/instances/$(L)_001.txt" - ig = ising_graph(instance) - set_prop!(ig, :rank, [3,2,5,4]) + set_prop!(ig, :rank, [3, 2, 5, 4]) rank = get_prop(ig, :rank) all = prod(rank) @@ -203,15 +191,12 @@ end instance_dict = Dict() ising = CSV.File(instance, types=[Int, Int, Float64], header=0, comment = "#") - for (i, j, v) ∈ ising - push!(instance_dict, (i, j) => v) - end + for (i, j, v) ∈ ising push!(instance_dict, (i, j) => v) end ig = ising_graph(instance) ig_dict = ising_graph(instance_dict) @test nv(ig_dict) == nv(ig) - @test collect(edges(ig)) == collect(edges(ig_dict)) end @@ -223,7 +208,6 @@ end β = 1 instance = "$(@__DIR__)/instances/pathological/test_$(m)_$(n)_$(t).txt" - ising = CSV.File(instance, types=[Int, Int, Float64], header=0, comment = "#") ig = ising_graph(instance) @@ -231,24 +215,18 @@ end -1 1 1 -1 -1 -1 1 1 1 -1 1 1 -1 1 -1 1; -1 1 1 -1 -1 -1 1 1 1 -1 1 1 -1 1 -1 -1; -1 1 1 -1 -1 1 1 1 1 -1 1 1 -1 1 -1 1; - -1 1 1 -1 -1 1 1 1 1 -1 1 1 -1 1 -1 -1] - + -1 1 1 -1 -1 1 1 1 1 -1 1 1 -1 1 -1 -1 + ] eng = _energy(ig, conf) - couplings = Dict() - for (i, j, v) ∈ ising - push!(couplings, (i, j) => v) - end + for (i, j, v) ∈ ising push!(couplings, (i, j) => v) end cedges = Dict() push!(cedges, (1, 2) => [(1, 4), (1, 5), (1, 6)]) push!(cedges, (1, 5) => [(1, 13)]) - push!(cedges, (2, 3) => [(4, 7), (5, 7), (6, 8), (6, 9)]) push!(cedges, (2, 6) => [(6, 16), (6, 18), (5, 16)]) - push!(cedges, (5, 6) => [(13, 16), (13, 18)]) - push!(cedges, (6, 10) => [(18, 28)]) push!( cedges, @@ -303,17 +281,17 @@ end num_config = length(config[1]) exact_energy = _energy(config, couplings, cedges, num_config) - low_energies = [-16.4, -16.4, -16.4, -16.4, -16.1, -16.1, -16.1, -16.1, -15.9, -15.9, -15.9, -15.9, -15.9, -15.9, -15.6, -15.6, -15.6, -15.6, -15.6, -15.6, -15.4, -15.4] - - for i ∈ 1:num_config - @test exact_energy[i] == low_energies[i] == eng[i] - end - + low_energies = [-16.4, -16.4, -16.4, -16.4, -16.1, + -16.1, -16.1, -16.1, -15.9, -15.9, + -15.9, -15.9, -15.9, -15.9, -15.6, + -15.6, -15.6, -15.6, -15.6, -15.6, + -15.4, -15.4 + ] + for i ∈ 1:num_config @test exact_energy[i] == low_energies[i] == eng[i] end end end @testset "Pruning" begin - @testset "No vertices of degree zero" begin instance = Dict( (1, 1) => 0.1, @@ -322,29 +300,20 @@ end (4, 2) => 1.0, (1, 2) => -0.3, ) - ig = ising_graph(instance) ng = prune(ig) @test nv(ig) == nv(ng) end @testset "All vertices of degree zero with no local fields" begin - instance = Dict( - (1, 1) => 0.0, - (2, 2) => 0.0, - ) - + instance = Dict((1, 1) => 0.0, (2, 2) => 0.0) ig = ising_graph(instance) ng = prune(ig) @test nv(ng) == 0 end @testset "All vertices of degree zero, but with local fields" begin - instance = Dict( - (1, 1) => 0.1, - (2, 2) => 0.5, - ) - + instance = Dict((1, 1) => 0.1, (2, 2) => 0.5) ig = ising_graph(instance) ng = prune(ig) @test nv(ng) == 2 @@ -358,11 +327,9 @@ end (4, 2) => 1.0, (1, 2) => -0.3, (5, 5) => 0.1 - ) - + ) ig = ising_graph(instance) ng = prune(ig) - @test nv(ng) == nv(ig) @test vertices(ng) == collect(1:nv(ng)) end @@ -375,11 +342,9 @@ end (4, 2) => 1.0, (1, 2) => -0.3, (5, 5) => 0.0 - ) - + ) ig = ising_graph(instance) ng = prune(ig) - @test nv(ng) == nv(ig) - 1 @test vertices(ng) == collect(1:nv(ng)) end diff --git a/test/runtests.jl b/test/runtests.jl index a152a6e..bd783a3 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -7,11 +7,6 @@ using Test Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) -idx(σ::Int) = (σ == -1) ? 1 : σ + 1 -energy(σ::Vector, J::Matrix, η::Vector=σ) = dot(σ, J, η) -energy(σ::Vector, h::Vector) = dot(h, σ) -energy(σ::Vector, ig::IsingGraph) = energy(σ, couplings(ig)) + energy(σ, biases(ig)) - my_tests = ["ising.jl", "factor.jl"] for my_test ∈ my_tests From b176c425c6b5e8d1ffea393994e2ca8152ee07ac Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 7 Dec 2021 18:57:28 +0100 Subject: [PATCH 049/218] clean up tests --- benchmarks/spectrum.jl | 4 ++-- src/ising.jl | 2 +- src/spectrum.jl | 12 +++++----- test/factor.jl | 2 +- test/ising.jl | 50 ++++++++++-------------------------------- 5 files changed, 22 insertions(+), 48 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 3da6083..db08921 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -11,7 +11,7 @@ function bench(instance::String, max_states::Int=100) ig = ising_graph(instance) cl = split_into_clusters(ig, super_square_lattice((m, n, t))) @time sp = brute_force(cl[1, 1], num_states=max_states) - sp + return end -sp = bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt"); +bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt") diff --git a/src/ising.jl b/src/ising.jl index d90b6cf..3028f10 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -50,7 +50,7 @@ biases(ig::IsingGraph) = get_prop.(Ref(ig), vertices(ig), :h) function couplings(ig::IsingGraph) J = zeros(nv(ig), nv(ig)) - for edge in edges(ig) + for edge ∈ edges(ig) i, j = ig.reverse_label_map[src(edge)], ig.reverse_label_map[dst(edge)] @inbounds J[i, j] = get_prop(ig, edge, :J) end diff --git a/src/spectrum.jl b/src/spectrum.jl index 35eacda..d87bbe9 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -11,20 +11,22 @@ struct Spectrum states::AbstractArray{State} end -energy(σ::State, ig::IsingGraph) = dot(σ, couplings(ig), σ) + dot(biases(ig), σ) function energy(σ::AbstractArray{State}, ig::IsingGraph) - J = couplings(ig), h = biases(ig) + J, h = couplings(ig), biases(ig) dot.(σ, Ref(J), σ) + dot.(Ref(h), σ) end function Spectrum(ig::IsingGraph) L = nv(ig) N = 2^L + energies = zeros(Float64, N) states = Vector{State}(undef, N) + + J, h = couplings(ig), biases(ig) Threads.@threads for i = 0:N-1 σ = 2 .* digits(i, base=2, pad=L) .- 1 - @inbounds energies[i+1] = energy(σ, ig) + @inbounds energies[i+1] = dot(σ, J, σ) + dot(h, σ) @inbounds states[i+1] = σ end Spectrum(energies, states) @@ -32,7 +34,7 @@ end function gibbs_tensor(ig::IsingGraph, β::Real=1.0) σ = collect.(all_states(rank_vec(ig))) - ρ = exp.(-β .* energy.(σ, Ref(ig))) + ρ = exp.(-β .* energy(σ, ig)) ρ ./ sum(ρ) end @@ -54,7 +56,7 @@ function full_spectrum(ig::IsingGraph; num_states::Int=1) ig_rank = rank_vec(ig) num_states = min(num_states, prod(ig_rank)) σ = collect.(all_states(ig_rank)) - energies = energy.(σ, Ref(ig)) + energies = energy(σ, ig) Spectrum(energies[begin:num_states], σ[begin:num_states]) end diff --git a/test/factor.jl b/test/factor.jl index cfbb619..8750699 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -257,6 +257,6 @@ end for (k, v) ∈ d spins[k] = v end - @test factor_graph_energy(fg, state) ≈ energy(Int.(spins), ig) + @test factor_graph_energy(fg, state) ≈ energy([Int.(spins)], ig)[] end end diff --git a/test/ising.jl b/test/ising.jl index 2cd7235..6b5c8dc 100644 --- a/test/ising.jl +++ b/test/ising.jl @@ -2,7 +2,6 @@ using CSV using LinearAlgebra using LabelledGraphs - function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) eng = zeros(1,n) for (i, j) ∈ keys(cedges) @@ -22,29 +21,13 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) eng end -function _energy(ig::LabelledGraph, config::Array) - s = size(config, 1) - eng = zeros(s) - for i ∈ 1:s - eng[i] = energy(config[i, :], ig) - end - eng -end - @testset "Ising graph cannot be created" begin - @testset "if input instance contains duplicate edges" begin @test_throws ArgumentError ising_graph( - Dict( - (1, 1) => 2.0, - (1, 2) => 0.5, - (2, 1) => -1.0 - ) - ) + Dict((1, 1) => 2.0, (1, 2) => 0.5, (2, 1) => -1.0)) end end - for (instance, source) ∈ ( ("$(@__DIR__)/instances/example.txt", "file"), ( @@ -66,11 +49,7 @@ for (instance, source) ∈ ( LabelledEdge(1, 4) => -2.0, LabelledEdge(2, 4) => 1.0 ) - expected_J_matrix = [ - [0 -0.3 -2.0]; - [0 0 1.0]; - [0 0 0]; - ] + expected_J_matrix = [[0 -0.3 -2.0]; [0 0 1.0]; [0 0 0]] ig = ising_graph(instance) @@ -97,7 +76,6 @@ for (instance, source) ∈ ( end end - @testset "Ising graph created with additional parameters" begin expected_biases = [-0.1, -0.5, 0.0] expected_couplings = Dict( @@ -149,28 +127,22 @@ end @testset "Naive brute force for +/-1" begin k = 2^N sp = brute_force(ig, num_states=k) - s = 5 - - @test sp.energies ≈ energy.(sp.states, Ref(ig)) β = rand(Float64) ρ = gibbs_tensor(ig, β) - @test size(ρ) == Tuple(fill(2, N)) - r = exp.(-β .* sp.energies) R = r ./ sum(r) - @test sum(R) ≈ 1 - @test sum(ρ) ≈ 1 - + @test size(ρ) == Tuple(fill(2, N)) + @test sum(R) ≈ sum(ρ) ≈ 1 + @test sp.energies ≈ energy(sp.states, ig) @test [ρ[idx.(σ)...] for σ ∈ sp.states] ≈ R end @testset "Naive brute force for general spins" begin L = 4 - instance = "$(@__DIR__)/instances/$(L)_001.txt" - ig = ising_graph(instance) + ig = ising_graph("$(@__DIR__)/instances/$(L)_001.txt") set_prop!(ig, :rank, [3, 2, 5, 4]) rank = get_prop(ig, :rank) @@ -212,12 +184,12 @@ end ig = ising_graph(instance) conf = [ - -1 1 1 -1 -1 -1 1 1 1 -1 1 1 -1 1 -1 1; - -1 1 1 -1 -1 -1 1 1 1 -1 1 1 -1 1 -1 -1; - -1 1 1 -1 -1 1 1 1 1 -1 1 1 -1 1 -1 1; - -1 1 1 -1 -1 1 1 1 1 -1 1 1 -1 1 -1 -1 + [-1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, -1, 1, -1, 1], + [-1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, -1, 1, -1, -1], + [-1, 1, 1, -1, -1, 1, 1, 1, 1, -1, 1, 1, -1, 1, -1, 1], + [-1, 1, 1, -1, -1, 1, 1, 1, 1, -1, 1, 1, -1, 1, -1, -1] ] - eng = _energy(ig, conf) + eng = energy(conf, ig) couplings = Dict() for (i, j, v) ∈ ising push!(couplings, (i, j) => v) end From fe15645e33db226292cecfed227426fc86db8202 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 7 Dec 2021 18:59:23 +0100 Subject: [PATCH 050/218] clean up 2 --- test/ising.jl | 19 ------------------- test/runtests.jl | 19 +++++++++++++++++++ 2 files changed, 19 insertions(+), 19 deletions(-) diff --git a/test/ising.jl b/test/ising.jl index 6b5c8dc..15933cc 100644 --- a/test/ising.jl +++ b/test/ising.jl @@ -2,25 +2,6 @@ using CSV using LinearAlgebra using LabelledGraphs -function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) - eng = zeros(1,n) - for (i, j) ∈ keys(cedges) - for (k, l) ∈ values(cedges[i, j]) - for m ∈ 1:length(config[k]) - s = config[k][m] - r = config[l][m] - J = couplings[k, l] - if k == l - eng[m] += dot(s, J) - else - eng[m] += dot(s, J, r) - end - end - end - end - eng -end - @testset "Ising graph cannot be created" begin @testset "if input instance contains duplicate edges" begin @test_throws ArgumentError ising_graph( diff --git a/test/runtests.jl b/test/runtests.jl index bd783a3..32eea43 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -7,6 +7,25 @@ using Test Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) +function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) + eng = zeros(1,n) + for (i, j) ∈ keys(cedges) + for (k, l) ∈ values(cedges[i, j]) + for m ∈ 1:length(config[k]) + s = config[k][m] + r = config[l][m] + J = couplings[k, l] + if k == l + eng[m] += dot(s, J) + else + eng[m] += dot(s, J, r) + end + end + end + end + eng +end + my_tests = ["ising.jl", "factor.jl"] for my_test ∈ my_tests From 668b4c9f621fed151e26593e068b3924ab444e9b Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 7 Dec 2021 19:02:56 +0100 Subject: [PATCH 051/218] clean up benchmarks --- benchmarks/spectrum.jl | 13 ++++--------- 1 file changed, 4 insertions(+), 9 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index db08921..8cf5653 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -1,17 +1,12 @@ using SpinGlassNetworks -function bench(instance::String, max_states::Int=100) - m = 2 - n = 2 - t = 24 - - println("Threads: ", Threads.nthreads()) - +function bench(instance::String, size::NTuple{3, Int}, max_states::Int=100) ig = ising_graph(instance) - cl = split_into_clusters(ig, super_square_lattice((m, n, t))) + cl = split_into_clusters(ig, super_square_lattice(size)) @time sp = brute_force(cl[1, 1], num_states=max_states) return end -bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt") +println("Threads: ", Threads.nthreads()) +bench("$(@__DIR__)/pegasus_droplets/2_2_3_00.txt", (2, 2, 24)) From b4ab708039746c1afead6f5c98fd7e06323e8e48 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 7 Dec 2021 19:09:36 +0100 Subject: [PATCH 052/218] clean factor.jl --- benchmarks/spectrum.jl | 2 +- src/factor.jl | 6 ++---- 2 files changed, 3 insertions(+), 5 deletions(-) diff --git a/benchmarks/spectrum.jl b/benchmarks/spectrum.jl index 8cf5653..cc241da 100644 --- a/benchmarks/spectrum.jl +++ b/benchmarks/spectrum.jl @@ -5,7 +5,7 @@ function bench(instance::String, size::NTuple{3, Int}, max_states::Int=100) ig = ising_graph(instance) cl = split_into_clusters(ig, super_square_lattice(size)) @time sp = brute_force(cl[1, 1], num_states=max_states) - return + nothing end println("Threads: ", Threads.nthreads()) diff --git a/src/factor.jl b/src/factor.jl index 660b580..8255125 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -44,11 +44,9 @@ function factor_graph( states_v = get_prop(fg, v, :spectrum).states states_w = get_prop(fg, w, :spectrum).states - reduced_states_v = [s[ind1] for s in states_v] - reduced_states_w = [s[ind2] for s in states_w] - pl, unique_states_v = rank_reveal(reduced_states_v, :PE) - pr, unique_states_w = rank_reveal(reduced_states_w, :PE) + pl, unique_states_v = rank_reveal([s[ind1] for s ∈ states_v], :PE) + pr, unique_states_w = rank_reveal([s[ind2] for s ∈ states_w], :PE) en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) add_edge!(fg, v, w) From 73cfe5c8e0c2ad5cc039062727dd79cd43bf25b4 Mon Sep 17 00:00:00 2001 From: Marek Rams Date: Thu, 9 Dec 2021 13:22:25 +0100 Subject: [PATCH 053/218] introducing Pegasus geometry --- src/lattice.jl | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/src/lattice.jl b/src/lattice.jl index 3664bfe..5d4b739 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -1,4 +1,4 @@ -export super_square_lattice +export super_square_lattice, pegasus_lattice function super_square_lattice(size::NTuple{5, Int}) m, um, n, un, t = size @@ -10,3 +10,14 @@ function super_square_lattice(size::NTuple{3, Int}) m, n, t = size super_square_lattice((m, 1, n, 1, t)) end + + +function pegasus_lattice(size::NTuple{2, Int}) + m, n = size + old = LinearIndices((1:24, 1:n, 1:m)) + map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ [1, 2, 3, 4, 9, 10, 11, 12, 17, 18, 19, 20]) + for i=1:m, j=1:n, k ∈ [5, 6, 7, 8, 13, 14, 15, 16, 21, 22, 23, 24] + push!(map, old[k, j, i] => (i, j, 2)) + end + map +end \ No newline at end of file From 7a5f65a910fb04146c01a201f7654948725dca06 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 9 Dec 2021 17:55:18 +0100 Subject: [PATCH 054/218] clean up pegasus_lattice --- src/lattice.jl | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 5d4b739..69e4202 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -11,13 +11,10 @@ function super_square_lattice(size::NTuple{3, Int}) super_square_lattice((m, 1, n, 1, t)) end - function pegasus_lattice(size::NTuple{2, Int}) m, n = size old = LinearIndices((1:24, 1:n, 1:m)) - map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ [1, 2, 3, 4, 9, 10, 11, 12, 17, 18, 19, 20]) - for i=1:m, j=1:n, k ∈ [5, 6, 7, 8, 13, 14, 15, 16, 21, 22, 23, 24] - push!(map, old[k, j, i] => (i, j, 2)) - end + map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ vcat(1:4, 9:12, 17:20)) + for i=1:m, j=1:n, k ∈ vcat(5:8, 13:16, 21:24) push!(map, old[k, j, i] => (i, j, 2)) end map -end \ No newline at end of file +end From 2622b89f8deafd46a219b8e63f98fef72108b8b2 Mon Sep 17 00:00:00 2001 From: Marek Rams Date: Fri, 10 Dec 2021 14:09:04 +0100 Subject: [PATCH 055/218] towards new pegasus geometry --- src/lattice.jl | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 69e4202..0fbe32b 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -14,7 +14,16 @@ end function pegasus_lattice(size::NTuple{2, Int}) m, n = size old = LinearIndices((1:24, 1:n, 1:m)) - map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ vcat(1:4, 9:12, 17:20)) - for i=1:m, j=1:n, k ∈ vcat(5:8, 13:16, 21:24) push!(map, old[k, j, i] => (i, j, 2)) end + map = Dict(old[k, j, i] => (i, 2*j-1) for i=1:m, j=1:n, k ∈ vcat(1:4, 9:12, 17:20)) + for i=1:m, j=1:n, k ∈ vcat(5:8, 13:16, 21:24) push!(map, old[k, j, i] => (i, 2*j)) end map end + +function pegasus_lattice(size::NTuple{3, Int}) + m, n, t = size # t is number of chimera units + old = LinearIndices((1:8*t, 1:n, 1:m)) + map = Dict(old[k, j, i] => (i, 2*j-1) for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 1:4)) + for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 5:8) push!(map, old[k, j, i] => (i, 2*j)) end + map +end + From b3ecd0b3254ef3c042446955af5f58f9ae4adba2 Mon Sep 17 00:00:00 2001 From: Marek Rams Date: Tue, 21 Dec 2021 20:54:24 +0100 Subject: [PATCH 056/218] new indexing of pegasus lattice --- src/lattice.jl | 26 ++++++++++++++++++++++---- 1 file changed, 22 insertions(+), 4 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 0fbe32b..02a6a56 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -11,19 +11,37 @@ function super_square_lattice(size::NTuple{3, Int}) super_square_lattice((m, 1, n, 1, t)) end +# function pegasus_lattice(size::NTuple{2, Int}) +# m, n = size +# old = LinearIndices((1:24, 1:n, 1:m)) +# map = Dict(old[k, j, i] => (i, 2*j-1) for i=1:m, j=1:n, k ∈ vcat(1:4, 9:12, 17:20)) +# for i=1:m, j=1:n, k ∈ vcat(5:8, 13:16, 21:24) push!(map, old[k, j, i] => (i, 2*j)) end +# map +# end + +# function pegasus_lattice(size::NTuple{3, Int}) +# m, n, t = size # t is number of chimera units +# old = LinearIndices((1:8*t, 1:n, 1:m)) +# map = Dict(old[k, j, i] => (i, 2*j-1) for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 1:4)) +# for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 5:8) push!(map, old[k, j, i] => (i, 2*j)) end +# map +# end + + function pegasus_lattice(size::NTuple{2, Int}) m, n = size old = LinearIndices((1:24, 1:n, 1:m)) - map = Dict(old[k, j, i] => (i, 2*j-1) for i=1:m, j=1:n, k ∈ vcat(1:4, 9:12, 17:20)) - for i=1:m, j=1:n, k ∈ vcat(5:8, 13:16, 21:24) push!(map, old[k, j, i] => (i, 2*j)) end + map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ vcat(1:4, 9:12, 17:20)) + for i=1:m, j=1:n, k ∈ vcat(5:8, 13:16, 21:24) push!(map, old[k, j, i] => (i, j, 2)) end map end function pegasus_lattice(size::NTuple{3, Int}) m, n, t = size # t is number of chimera units old = LinearIndices((1:8*t, 1:n, 1:m)) - map = Dict(old[k, j, i] => (i, 2*j-1) for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 1:4)) - for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 5:8) push!(map, old[k, j, i] => (i, 2*j)) end + map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 1:4)) + for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 5:8) push!(map, old[k, j, i] => (i, j, 2)) end map end + From 2efd070e63eba76a06a5936c4e359b147dfac946 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 21 Dec 2021 20:56:16 +0100 Subject: [PATCH 057/218] clean up --- src/lattice.jl | 27 ++++++--------------------- 1 file changed, 6 insertions(+), 21 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 02a6a56..7d53d07 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -11,23 +11,6 @@ function super_square_lattice(size::NTuple{3, Int}) super_square_lattice((m, 1, n, 1, t)) end -# function pegasus_lattice(size::NTuple{2, Int}) -# m, n = size -# old = LinearIndices((1:24, 1:n, 1:m)) -# map = Dict(old[k, j, i] => (i, 2*j-1) for i=1:m, j=1:n, k ∈ vcat(1:4, 9:12, 17:20)) -# for i=1:m, j=1:n, k ∈ vcat(5:8, 13:16, 21:24) push!(map, old[k, j, i] => (i, 2*j)) end -# map -# end - -# function pegasus_lattice(size::NTuple{3, Int}) -# m, n, t = size # t is number of chimera units -# old = LinearIndices((1:8*t, 1:n, 1:m)) -# map = Dict(old[k, j, i] => (i, 2*j-1) for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 1:4)) -# for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 5:8) push!(map, old[k, j, i] => (i, 2*j)) end -# map -# end - - function pegasus_lattice(size::NTuple{2, Int}) m, n = size old = LinearIndices((1:24, 1:n, 1:m)) @@ -39,9 +22,11 @@ end function pegasus_lattice(size::NTuple{3, Int}) m, n, t = size # t is number of chimera units old = LinearIndices((1:8*t, 1:n, 1:m)) - map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 1:4)) - for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 5:8) push!(map, old[k, j, i] => (i, j, 2)) end + map = Dict( + old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 1:4) + ) + for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 5:8) + push!(map, old[k, j, i] => (i, j, 2)) + end map end - - From e8a86e0ddfb749a0cb0a0eb1a71ab6bec1253f83 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 14:09:28 +0100 Subject: [PATCH 058/218] add energy --- src/factor.jl | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/src/factor.jl b/src/factor.jl index 8255125..cc3ed06 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -86,3 +86,14 @@ function decode_factor_graph_state(fg, state::Vector{Int}) end ret end + +function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) + spins = decode_factor_graph_state(fg, fg_state) + en = 0.0 + J, h = couplings(ig), biases(ig) + for (i, σ) ∈ spins + en += h[i] * σ + for (j, η) ∈ spins en += σ * J[i, j] * η end + end + en +end From d540ece3e5959e5ca9852ab86aac222f90520847 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 14:20:38 +0100 Subject: [PATCH 059/218] fix up --- src/factor.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index cc3ed06..2224480 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -92,8 +92,8 @@ function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) en = 0.0 J, h = couplings(ig), biases(ig) for (i, σ) ∈ spins - en += h[i] * σ - for (j, η) ∈ spins en += σ * J[i, j] * η end + en += get_prop(ig, i, :h) * σ + for (j, η) ∈ spins en += σ * get_prop(ig, i, j, :J) * η end end en end From b12f361bf038851079814bd2a6657be4325257e6 Mon Sep 17 00:00:00 2001 From: Marek Rams Date: Thu, 23 Dec 2021 14:37:37 +0100 Subject: [PATCH 060/218] energy in factor --- src/factor.jl | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 2224480..04f3ce8 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -93,7 +93,13 @@ function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) J, h = couplings(ig), biases(ig) for (i, σ) ∈ spins en += get_prop(ig, i, :h) * σ - for (j, η) ∈ spins en += σ * get_prop(ig, i, j, :J) * η end + for (j, η) ∈ spins + if has_edge(ig, (i, j)) + en += σ * get_prop(ig, i, j, :J) * η + elseif has_edge(ig, (j, i)) + en += σ * get_prop(ig, j, i, :J) * η + end + end end en end From 2587379aeabe3e03b37e58d8dc785a3ab5d5ab60 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 14:50:17 +0100 Subject: [PATCH 061/218] fix energy --- src/factor.jl | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 04f3ce8..3a8830c 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -88,17 +88,15 @@ function decode_factor_graph_state(fg, state::Vector{Int}) end function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) - spins = decode_factor_graph_state(fg, fg_state) + ig_states = decode_factor_graph_state(fg, fg_state) en = 0.0 J, h = couplings(ig), biases(ig) - for (i, σ) ∈ spins + for (i, σ) ∈ ig_states en += get_prop(ig, i, :h) * σ - for (j, η) ∈ spins - if has_edge(ig, (i, j)) - en += σ * get_prop(ig, i, j, :J) * η - elseif has_edge(ig, (j, i)) - en += σ * get_prop(ig, j, i, :J) * η - end + for (j, η) ∈ ig_states + e = Egde(i, j) + J = has_edge(ig, e) ? get_prop(ig, e, :J) : get_prop(ig, j, i, :J) + en += σ * J * η end end en From 889e9f2faa97ab824a55a35e3e68faa014fe0e59 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 14:50:50 +0100 Subject: [PATCH 062/218] clean up --- src/factor.jl | 1 - 1 file changed, 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 3a8830c..b6eb891 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -90,7 +90,6 @@ end function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) ig_states = decode_factor_graph_state(fg, fg_state) en = 0.0 - J, h = couplings(ig), biases(ig) for (i, σ) ∈ ig_states en += get_prop(ig, i, :h) * σ for (j, η) ∈ ig_states From b17b9f75741078af9cd5ac6454d36ae89d71651d Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 14:59:17 +0100 Subject: [PATCH 063/218] clean up --- src/factor.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index b6eb891..191517f 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -94,7 +94,7 @@ function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) en += get_prop(ig, i, :h) * σ for (j, η) ∈ ig_states e = Egde(i, j) - J = has_edge(ig, e) ? get_prop(ig, e, :J) : get_prop(ig, j, i, :J) + J = has_edge(ig, e) ? get_prop(ig, e, :J) : get_prop(ig, Egde(j, i), :J) en += σ * J * η end end From 7ff9d00ce5106eeef1762d7acc89f7d33733faeb Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 15:12:43 +0100 Subject: [PATCH 064/218] add comment --- src/factor.jl | 1 + 1 file changed, 1 insertion(+) diff --git a/src/factor.jl b/src/factor.jl index 191517f..728ef92 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -87,6 +87,7 @@ function decode_factor_graph_state(fg, state::Vector{Int}) ret end +#TODO: improve this using dot function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) ig_states = decode_factor_graph_state(fg, fg_state) en = 0.0 From abe2c364cffb7d76995b7188f048624b0b934ebd Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 15:26:52 +0100 Subject: [PATCH 065/218] fix --- src/factor.jl | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 728ef92..9debc2c 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -94,8 +94,7 @@ function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) for (i, σ) ∈ ig_states en += get_prop(ig, i, :h) * σ for (j, η) ∈ ig_states - e = Egde(i, j) - J = has_edge(ig, e) ? get_prop(ig, e, :J) : get_prop(ig, Egde(j, i), :J) + J = has_edge(ig, i, j) ? get_prop(ig, i, j, :J) : get_prop(ig, j, i, :J) en += σ * J * η end end From 72b54df66811d3ae0e152b0823c876a588964bb3 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 15:33:04 +0100 Subject: [PATCH 066/218] ecv From 3ad8684a1ba8f0e7d59be6c838e9f9936185e4fb Mon Sep 17 00:00:00 2001 From: Marek Rams Date: Thu, 23 Dec 2021 15:42:47 +0100 Subject: [PATCH 067/218] energy fg to fix --- src/factor.jl | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 728ef92..9debc2c 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -94,8 +94,7 @@ function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) for (i, σ) ∈ ig_states en += get_prop(ig, i, :h) * σ for (j, η) ∈ ig_states - e = Egde(i, j) - J = has_edge(ig, e) ? get_prop(ig, e, :J) : get_prop(ig, Egde(j, i), :J) + J = has_edge(ig, i, j) ? get_prop(ig, i, j, :J) : get_prop(ig, j, i, :J) en += σ * J * η end end From dcff7ca6ef67938b49f46e9305b5e28e7b5c788e Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 20:58:58 +0100 Subject: [PATCH 068/218] add energy for factor graph --- src/factor.jl | 16 ++++------------ 1 file changed, 4 insertions(+), 12 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 9debc2c..93e717b 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -87,16 +87,8 @@ function decode_factor_graph_state(fg, state::Vector{Int}) ret end -#TODO: improve this using dot -function energy(ig::IsingGraph, fg, fg_state::Vector{Int}) - ig_states = decode_factor_graph_state(fg, fg_state) - en = 0.0 - for (i, σ) ∈ ig_states - en += get_prop(ig, i, :h) * σ - for (j, η) ∈ ig_states - J = has_edge(ig, i, j) ? get_prop(ig, i, j, :J) : get_prop(ig, j, i, :J) - en += σ * J * η - end - end - en +function energy(J::AbstractMatrix{<:Real}, fg, fg_state::Vector{Int}) + σ = zeros(size(J, 1)) + for (i, s) ∈ decode_factor_graph_state(fg, fg_state) @inbounds σ[i] = s end + dot(σ, J, σ) end From 526edad531ab8bb1aed824454b741edf4ba7e6dd Mon Sep 17 00:00:00 2001 From: Bartek Gardas Date: Thu, 23 Dec 2021 23:35:56 +0100 Subject: [PATCH 069/218] add energy From bdb082c3c4c83e9cca84924227416e1d66e3ecb9 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 23 Dec 2021 23:44:50 +0100 Subject: [PATCH 070/218] add energy --- src/factor.jl | 21 +++++++++++++++++---- 1 file changed, 17 insertions(+), 4 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 93e717b..0e3c3a5 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -87,8 +87,21 @@ function decode_factor_graph_state(fg, state::Vector{Int}) ret end -function energy(J::AbstractMatrix{<:Real}, fg, fg_state::Vector{Int}) - σ = zeros(size(J, 1)) - for (i, s) ∈ decode_factor_graph_state(fg, fg_state) @inbounds σ[i] = s end - dot(σ, J, σ) +function energy(ig::IsingGraph, fg::LabelledGraph, fg_state::Vector{Int}) + ig_state = decode_factor_graph_state(fg, fg_state) + en = 0.0 + for (i, σ) ∈ ig_state + en += get_prop(ig, i, :h) * σ + for (j, η) ∈ ig_state + if has_edge(ig, i, j) + J = get_prop(ig, i, j, :J) + elseif has_edge(ig, j, i) + J = get_prop(ig, j, i, :J) + else + J = 0.0 + end + en += σ * J * η / 2.0 + end + end + en end From 6bbdba51b17886f253d66fcc7a00bd913c9eddf3 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Fri, 24 Dec 2021 00:20:39 +0100 Subject: [PATCH 071/218] fix energy --- src/factor.jl | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 0e3c3a5..23537ad 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -87,20 +87,16 @@ function decode_factor_graph_state(fg, state::Vector{Int}) ret end -function energy(ig::IsingGraph, fg::LabelledGraph, fg_state::Vector{Int}) - ig_state = decode_factor_graph_state(fg, fg_state) +function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en = 0.0 for (i, σ) ∈ ig_state en += get_prop(ig, i, :h) * σ for (j, η) ∈ ig_state if has_edge(ig, i, j) - J = get_prop(ig, i, j, :J) + en += σ * get_prop(ig, i, j, :J) * η / 2.0 elseif has_edge(ig, j, i) - J = get_prop(ig, j, i, :J) - else - J = 0.0 + en += σ * get_prop(ig, j, i, :J) * η / 2.0 end - en += σ * J * η / 2.0 end end en From 787fe3cb4cbf2b781e67b86e71817335f7ac0a5b Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 11 Jan 2022 21:56:59 +0100 Subject: [PATCH 072/218] add changes for 1.7 --- Project.toml | 6 ++++-- src/SpinGlassNetworks.jl | 2 +- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/Project.toml b/Project.toml index 78135d8..3cc4808 100644 --- a/Project.toml +++ b/Project.toml @@ -1,6 +1,6 @@ name = "SpinGlassNetworks" uuid = "b7f6bd3e-55dc-4da6-96a9-ef9dbec6ac19" -authors = ["Krzysztof Domino ", "Anna Maria Dziubyna ", "Bartłomiej Gardas ", "Konrad Jałowiecki ", "Łukasz Pawela ", "Marek M. Rams "] +authors = ["Anna Maria Dziubyna ", "Bartłomiej Gardas ", "Konrad Jałowiecki ", "Łukasz Pawela ", "Marek M. Rams "] version = "0.2.3" [deps] @@ -9,6 +9,7 @@ DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae" LabelledGraphs = "605abd48-4d17-4660-b914-d4df33194460" LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" +MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2" MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5" [compat] @@ -17,7 +18,8 @@ DocStringExtensions = "0.8" LabelledGraphs = "0.3.2" LightGraphs = "1.3" MetaGraphs = "0.6" -julia = "1.5" +julia = "1.5, 1.6, 1.7" +MKL = "0.4.2" [extras] Logging = "56ddb016-857b-54e1-b83d-db4d58db5568" diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 9b53166..8106a92 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -4,7 +4,7 @@ module SpinGlassNetworks using MetaGraphs # TODO: remove that using CSV using DocStringExtensions - using LinearAlgebra + using LinearAlgebra, MKL using Base.Cartesian import Base.Prehashed From 48126ac05cc0d95ca60b757e478da7516350b05e Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 19 Jan 2022 14:27:36 +0100 Subject: [PATCH 073/218] add energy from factor graph --- src/factor.jl | 19 ++++++++++++++++++- 1 file changed, 18 insertions(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 23537ad..5b1ee73 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -1,5 +1,5 @@ export factor_graph, rank_reveal, projectors, split_into_clusters -export decode_factor_graph_state +export decode_factor_graph_state, energy function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} cluster_id_to_verts = Dict(i => T[] for i in values(assignment_rule)) @@ -101,3 +101,20 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) end en end + +function energy(fg::LabelledGraph, σ::Dict) + eng = 0 + for v ∈ vertices(fg) + en = get_prop(fg, v, :spectrum).energies + eng += en[σ[v]] #sigma Dict(vertices -> Int) + end + println(edges(fg)) + for (e,f) ∈ edges(fg) + #println() + E = get_prop(fg, e, f, :en) + Pf = get_prop(fg, e, f, :pr) + Pe = get_prop(fg, e, f, :pl) + eng += E[Pe[σ[e]], Pf[σ[f]]] + end + eng +end From d8b30838a3f0e75db5da1fd2012ba26e36a2a84f Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Wed, 19 Jan 2022 14:52:39 +0100 Subject: [PATCH 074/218] clean up energy --- src/factor.jl | 21 ++++++++------------- 1 file changed, 8 insertions(+), 13 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 5b1ee73..1906116 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -103,18 +103,13 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) end function energy(fg::LabelledGraph, σ::Dict) - eng = 0 - for v ∈ vertices(fg) - en = get_prop(fg, v, :spectrum).energies - eng += en[σ[v]] #sigma Dict(vertices -> Int) - end - println(edges(fg)) - for (e,f) ∈ edges(fg) - #println() - E = get_prop(fg, e, f, :en) - Pf = get_prop(fg, e, f, :pr) - Pe = get_prop(fg, e, f, :pl) - eng += E[Pe[σ[e]], Pf[σ[f]]] + en = 0.0 + for v ∈ vertices(fg) en += get_prop(fg, v, :spectrum).energies[σ[v]] end + for (e, f) ∈ edges(fg) + en_ef = get_prop(fg, e, f, :en) + pf = get_prop(fg, e, f, :pr) + pe = get_prop(fg, e, f, :pl) + en += en_ef[pe[σ[e]], pf[σ[f]]] end - eng + en end From c322836ea39c1609ef0f65c4954dbf60c70d2435 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 19 Jan 2022 15:21:18 +0100 Subject: [PATCH 075/218] energy works --- src/factor.jl | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 1906116..7bab5e7 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -105,11 +105,15 @@ end function energy(fg::LabelledGraph, σ::Dict) en = 0.0 for v ∈ vertices(fg) en += get_prop(fg, v, :spectrum).energies[σ[v]] end - for (e, f) ∈ edges(fg) - en_ef = get_prop(fg, e, f, :en) - pf = get_prop(fg, e, f, :pr) - pe = get_prop(fg, e, f, :pl) - en += en_ef[pe[σ[e]], pf[σ[f]]] + for e ∈ vertices(fg) + for f ∈ vertices(fg) + if has_edge(fg, e, f) + en_ef = get_prop(fg, e, f, :en) + pf = get_prop(fg, e, f, :pr) + pe = get_prop(fg, e, f, :pl) + en += en_ef[pe[σ[e]], pf[σ[f]]] + end + end end en end From 27234137d96976309c5f53745413a0614abcd712 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Wed, 19 Jan 2022 15:29:10 +0100 Subject: [PATCH 076/218] cleam up --- src/factor.jl | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 1906116..2f01ffd 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -107,8 +107,7 @@ function energy(fg::LabelledGraph, σ::Dict) for v ∈ vertices(fg) en += get_prop(fg, v, :spectrum).energies[σ[v]] end for (e, f) ∈ edges(fg) en_ef = get_prop(fg, e, f, :en) - pf = get_prop(fg, e, f, :pr) - pe = get_prop(fg, e, f, :pl) + pe, pf = get_prop(fg, e, f, :pl), get_prop(fg, e, f, :pr) en += en_ef[pe[σ[e]], pf[σ[f]]] end en From b35a3734bff5c0d40f594c185ad820c57bad8f33 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Wed, 19 Jan 2022 16:34:51 +0100 Subject: [PATCH 077/218] clean up --- src/factor.jl | 15 ++++++++++----- 1 file changed, 10 insertions(+), 5 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 2f01ffd..e0db465 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -104,11 +104,16 @@ end function energy(fg::LabelledGraph, σ::Dict) en = 0.0 - for v ∈ vertices(fg) en += get_prop(fg, v, :spectrum).energies[σ[v]] end - for (e, f) ∈ edges(fg) - en_ef = get_prop(fg, e, f, :en) - pe, pf = get_prop(fg, e, f, :pl), get_prop(fg, e, f, :pr) - en += en_ef[pe[σ[e]], pf[σ[f]]] + for e ∈ vertices(fg) + en += get_prop(fg, e, :spectrum).energies[σ[e]] + for f ∈ vertices(fg) + if has_edge(fg, e, f) + en_ef = get_prop(fg, e, f, :en) + pf = get_prop(fg, e, f, :pr) + pe = get_prop(fg, e, f, :pl) + en += en_ef[pe[σ[e]], pf[σ[f]]] + end + end end en end From b72d7484de21d02ee7347e16e2cb8087539b11b8 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Wed, 19 Jan 2022 20:03:18 +0100 Subject: [PATCH 078/218] simplify energy for fg --- src/factor.jl | 17 +++++++---------- 1 file changed, 7 insertions(+), 10 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index e0db465..fed8bc0 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -104,16 +104,13 @@ end function energy(fg::LabelledGraph, σ::Dict) en = 0.0 - for e ∈ vertices(fg) - en += get_prop(fg, e, :spectrum).energies[σ[e]] - for f ∈ vertices(fg) - if has_edge(fg, e, f) - en_ef = get_prop(fg, e, f, :en) - pf = get_prop(fg, e, f, :pr) - pe = get_prop(fg, e, f, :pl) - en += en_ef[pe[σ[e]], pf[σ[f]]] - end - end + for v ∈ vertices(fg) en += get_prop(fg, v, :spectrum).energies[σ[v]] end + for edge ∈ edges(fg) + en_ef = get_prop(fg, edge, :en) + pf = get_prop(fg, edge, :pr) + pe = get_prop(fg, edge, :pl) + u, v = src(edge), dst(edge) + en += en_ef[pe[σ[u]], pf[σ[v]]] end en end From d41602646ec6977558452cbb139786f0e7e3a09a Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Wed, 19 Jan 2022 20:31:47 +0100 Subject: [PATCH 079/218] clean up energy --- src/factor.jl | 16 +++++++--------- 1 file changed, 7 insertions(+), 9 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index fed8bc0..5660435 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -102,15 +102,13 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en end -function energy(fg::LabelledGraph, σ::Dict) - en = 0.0 - for v ∈ vertices(fg) en += get_prop(fg, v, :spectrum).energies[σ[v]] end +function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} + en_fg = 0.0 + for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end for edge ∈ edges(fg) - en_ef = get_prop(fg, edge, :en) - pf = get_prop(fg, edge, :pr) - pe = get_prop(fg, edge, :pl) - u, v = src(edge), dst(edge) - en += en_ef[pe[σ[u]], pf[σ[v]]] + pl, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) + en = get_prop(fg, edge, :en) + en_fg += en[pl[σ[src(edge)]], pr[σ[dst(edge)]]] end - en + en_fg end From 074f45a1fb648e35d0bf9f27cc123991fb07e41d Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 20 Jan 2022 14:28:07 +0100 Subject: [PATCH 080/218] energy --- src/factor.jl | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 5660435..3fba24d 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -102,7 +102,9 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en end -function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} +#function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} +function energy(fg::LabelledGraph, σ) + en_fg = 0.0 for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end for edge ∈ edges(fg) From 83f47f9780d511138b69972423fd705db914252f Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 20 Jan 2022 14:39:20 +0100 Subject: [PATCH 081/218] fix energy for fg --- src/factor.jl | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 5660435..09fd307 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -102,7 +102,8 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en end -function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} +#function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} +function energy(fg::LabelledGraph, σ::Dict) en_fg = 0.0 for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end for edge ∈ edges(fg) From bf443cdcf7f8981cef5d016674e6feae9c52aa9b Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 25 Jan 2022 19:49:14 +0100 Subject: [PATCH 082/218] clear types and add cluster_size for fg --- src/factor.jl | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 09fd307..f25936e 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -1,5 +1,5 @@ export factor_graph, rank_reveal, projectors, split_into_clusters -export decode_factor_graph_state, energy +export decode_factor_graph_state, energy, cluster_size function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} cluster_id_to_verts = Dict(i => T[] for i in values(assignment_rule)) @@ -102,8 +102,7 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en end -#function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} -function energy(fg::LabelledGraph, σ::Dict) +function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_fg = 0.0 for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end for edge ∈ edges(fg) @@ -113,3 +112,7 @@ function energy(fg::LabelledGraph, σ::Dict) end en_fg end + +function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} + length(get_prop(factor_graph, vertex, :spectrum).energies) +end From 47dd623b4bfd50f21e3ffb1654a65f2d74a558ab Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 27 Jan 2022 10:57:44 +0100 Subject: [PATCH 083/218] test --- src/factor.jl | 1 + 1 file changed, 1 insertion(+) diff --git a/src/factor.jl b/src/factor.jl index f25936e..f6915db 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -102,6 +102,7 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en end + function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_fg = 0.0 for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end From 110522037d455cd39d5bccf1676a4dc50cdf2157 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 10 Feb 2022 11:10:49 +0100 Subject: [PATCH 084/218] start documenting code --- src/factor.jl | 22 ++++++++++++++++++++++ src/ising.jl | 18 ++++++++++++------ src/lattice.jl | 11 +++-------- src/spectrum.jl | 2 ++ 4 files changed, 39 insertions(+), 14 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index f6915db..d5ddca1 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -1,12 +1,22 @@ export factor_graph, rank_reveal, projectors, split_into_clusters export decode_factor_graph_state, energy, cluster_size +""" +Groups spins into clusters, +Return: +Dict(factor graph coordinates -> group of spins in Ising graph) +""" function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} cluster_id_to_verts = Dict(i => T[] for i in values(assignment_rule)) for v in vertices(ig) push!(cluster_id_to_verts[assignment_rule[v]], v) end Dict(i => first(cluster(ig, verts)) for (i, verts) ∈ cluster_id_to_verts) end +""" +To how many states in each cluster truncate and create factor graph +Returns: + +""" function factor_graph( ig::IsingGraph, num_states_cl::Int; @@ -17,6 +27,9 @@ function factor_graph( factor_graph(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end +""" +Factor graph order introduced as a natural order in factor graph coordinates. +""" function factor_graph( ig::IsingGraph, num_states_cl::Dict{T, Int}; @@ -74,6 +87,12 @@ function rank_reveal(energy, order=:PE) order == :PE ? (P, E) : (E, P) end +""" +Assumes that state has the same order as vertices in factor graph. +Returns: +Dict(vertex of ising graph -> spin value) +TODO: check tha order consistency over packages +""" function decode_factor_graph_state(fg, state::Vector{Int}) ret = Dict{Int, Int}() for (i, vert) ∈ zip(state, vertices(fg)) @@ -87,6 +106,9 @@ function decode_factor_graph_state(fg, state::Vector{Int}) ret end +""" +TODO: write it better +""" function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en = 0.0 for (i, σ) ∈ ig_state diff --git a/src/ising.jl b/src/ising.jl index 3028f10..adf4506 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -10,6 +10,9 @@ function unique_nodes(ising_tuples) sort(collect(Set(Iterators.flatten((i, j) for (i, j, _) ∈ ising_tuples)))) end +""" +Assumes: H = sgn * J_{ij} * s_i * s_j + sgn * J_{ii} * s_i +""" function ising_graph( instance::Instance; sgn::Real=1.0, rank_override::Dict{Int, Int}=Dict{Int, Int}() ) @@ -20,11 +23,7 @@ function ising_graph( ising = [(i, j, J) for ((i, j), J) ∈ instance] end - nodes = unique_nodes(ising) - L = length(nodes) - nodes_to_vertices = Dict(w => i for (i, w) ∈ enumerate(nodes)) - - ig = LabelledGraph{MetaGraph}(nodes) + ig = LabelledGraph{MetaGraph}(unique_nodes(ising)) set_prop!.(Ref(ig), vertices(ig), :h, 0) foreach(v -> set_prop!(ig, v, :rank, get(rank_override, v, 2)), vertices(ig)) @@ -45,7 +44,7 @@ function ising_graph( ig end rank_vec(ig::IsingGraph) = Int[get_prop((ig), v, :rank) for v ∈ vertices(ig)] -basis_size(ig::IsingGraph) = prod(prod(rank_vec(ig))) +basis_size(ig::IsingGraph) = prod(rank_vec(ig)) biases(ig::IsingGraph) = get_prop.(Ref(ig), vertices(ig), :h) function couplings(ig::IsingGraph) @@ -58,6 +57,9 @@ function couplings(ig::IsingGraph) end cluster(ig::IsingGraph, verts) = induced_subgraph(ig, collect(verts)) +""" +Returns dense adjacency matrix +""" function inter_cluster_edges(ig::IsingGraph, cl1::IsingGraph, cl2::IsingGraph) verts1, verts2 = vertices(cl1), vertices(cl2) @@ -73,6 +75,10 @@ function inter_cluster_edges(ig::IsingGraph, cl1::IsingGraph, cl2::IsingGraph) outer_edges, J end +""" +Get rid of non-existing spins? +Used only in MPS_search, would be obsolete if MPS_search uses QMps. +""" function prune(ig::IsingGraph) to_keep = vcat( findall(!iszero, degree(ig)), diff --git a/src/lattice.jl b/src/lattice.jl index 7d53d07..3c042e9 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -1,6 +1,7 @@ export super_square_lattice, pegasus_lattice - function super_square_lattice(size::NTuple{5, Int}) +"Variable number of Ising graph -> Factor graph coordinate system" +function super_square_lattice(size::NTuple{5, Int}) m, um, n, un, t = size old = LinearIndices((1:t, 1:un, 1:n, 1:um, 1:m)) Dict(old[k, uj, j, ui, i] => (i, j) for i=1:m, ui=1:um, j=1:n, uj=1:un, k=1:t) @@ -11,13 +12,7 @@ function super_square_lattice(size::NTuple{3, Int}) super_square_lattice((m, 1, n, 1, t)) end -function pegasus_lattice(size::NTuple{2, Int}) - m, n = size - old = LinearIndices((1:24, 1:n, 1:m)) - map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ vcat(1:4, 9:12, 17:20)) - for i=1:m, j=1:n, k ∈ vcat(5:8, 13:16, 21:24) push!(map, old[k, j, i] => (i, j, 2)) end - map -end +pegasus_lattice(size::NTuple{2, Int}) = pegasus_lattice((size[1], size[2], 3)) function pegasus_lattice(size::NTuple{3, Int}) m, n, t = size # t is number of chimera units diff --git a/src/spectrum.jl b/src/spectrum.jl index d87bbe9..67e6c4b 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -32,6 +32,7 @@ function Spectrum(ig::IsingGraph) Spectrum(energies, states) end +#Only for testing purposes function gibbs_tensor(ig::IsingGraph, β::Real=1.0) σ = collect.(all_states(rank_vec(ig))) ρ = exp.(-β .* energy(σ, ig)) @@ -51,6 +52,7 @@ function brute_force(ig::IsingGraph, ::Val{:CPU}; num_states::Int=1) Spectrum(sp.energies[idx], sp.states[idx]) end +#TODO: to be removed function full_spectrum(ig::IsingGraph; num_states::Int=1) if nv(ig) == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end ig_rank = rank_vec(ig) From 7bcb4ebd7eb8be28e9400734089a7a2734f7b4a1 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Thu, 10 Feb 2022 16:39:41 +0100 Subject: [PATCH 085/218] start commenting code --- src/factor.jl | 22 +++++++--------------- src/ising.jl | 26 +++++++++++++++----------- 2 files changed, 22 insertions(+), 26 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index d5ddca1..fdd2c81 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -2,9 +2,7 @@ export factor_graph, rank_reveal, projectors, split_into_clusters export decode_factor_graph_state, energy, cluster_size """ -Groups spins into clusters, -Return: -Dict(factor graph coordinates -> group of spins in Ising graph) +Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} cluster_id_to_verts = Dict(i => T[] for i in values(assignment_rule)) @@ -13,9 +11,8 @@ function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, end """ -To how many states in each cluster truncate and create factor graph -Returns: - +Create factor graph. +Factor graph order introduced as a natural order in factor graph coordinates. """ function factor_graph( ig::IsingGraph, @@ -27,9 +24,6 @@ function factor_graph( factor_graph(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end -""" -Factor graph order introduced as a natural order in factor graph coordinates. -""" function factor_graph( ig::IsingGraph, num_states_cl::Dict{T, Int}; @@ -88,10 +82,9 @@ function rank_reveal(energy, order=:PE) end """ -Assumes that state has the same order as vertices in factor graph. -Returns: -Dict(vertex of ising graph -> spin value) -TODO: check tha order consistency over packages +Returns Dict(vertex of ising graph -> spin value) +Assumes that state has the same order as vertices in factor graph! +TODO: check the order consistency over external packages. """ function decode_factor_graph_state(fg, state::Vector{Int}) ret = Dict{Int, Int}() @@ -107,7 +100,7 @@ function decode_factor_graph_state(fg, state::Vector{Int}) end """ -TODO: write it better +TODO: write it better (for now this is only for testing). """ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en = 0.0 @@ -124,7 +117,6 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en end - function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_fg = 0.0 for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end diff --git a/src/ising.jl b/src/ising.jl index adf4506..c5af076 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -1,7 +1,16 @@ using LabelledGraphs -export ising_graph, rank_vec, cluster, rank, nodes, basis_size, biases, couplings -export IsingGraph, prune +export + ising_graph, + rank_vec, + cluster, + rank, + nodes, + basis_size, + biases, + couplings, + IsingGraph, + prune const Instance = Union{String, Dict} const IsingGraph = LabelledGraph{MetaGraph{Int64, Float64}, Int64} @@ -11,7 +20,7 @@ function unique_nodes(ising_tuples) end """ -Assumes: H = sgn * J_{ij} * s_i * s_j + sgn * J_{ii} * s_i +Creates Ising graph, H = sgn * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) """ function ising_graph( instance::Instance; sgn::Real=1.0, rank_override::Dict{Int, Int}=Dict{Int, Int}() @@ -22,7 +31,6 @@ function ising_graph( else ising = [(i, j, J) for ((i, j), J) ∈ instance] end - ig = LabelledGraph{MetaGraph}(unique_nodes(ising)) set_prop!.(Ref(ig), vertices(ig), :h, 0) @@ -37,14 +45,13 @@ function ising_graph( set_prop!(ig, i, j, :J, v) end end - set_prop!( ig, :rank, Dict{Int, Int}(v => get(rank_override, v, 2) for v in vertices(ig)) ) ig end rank_vec(ig::IsingGraph) = Int[get_prop((ig), v, :rank) for v ∈ vertices(ig)] -basis_size(ig::IsingGraph) = prod(rank_vec(ig)) +basis_size(ig::IsingGraph) = prod(rank_vec(ig)) biases(ig::IsingGraph) = get_prop.(Ref(ig), vertices(ig), :h) function couplings(ig::IsingGraph) @@ -58,15 +65,12 @@ end cluster(ig::IsingGraph, verts) = induced_subgraph(ig, collect(verts)) """ -Returns dense adjacency matrix +Returns dense adjacency matrix between clusters. """ function inter_cluster_edges(ig::IsingGraph, cl1::IsingGraph, cl2::IsingGraph) - verts1, verts2 = vertices(cl1), vertices(cl2) - outer_edges = [ LabelledEdge(i, j) for i ∈ vertices(cl1), j ∈ vertices(cl2) if has_edge(ig, i, j) ] - J = zeros(nv(cl1), nv(cl2)) for e ∈ outer_edges i, j = cl1.reverse_label_map[src(e)], cl2.reverse_label_map[dst(e)] @@ -76,7 +80,7 @@ function inter_cluster_edges(ig::IsingGraph, cl1::IsingGraph, cl2::IsingGraph) end """ -Get rid of non-existing spins? +Get rid of non-existing spins. Used only in MPS_search, would be obsolete if MPS_search uses QMps. """ function prune(ig::IsingGraph) From d7a06a7a91dc1f87d222588b0f7dea097b95a64b Mon Sep 17 00:00:00 2001 From: marekrams Date: Thu, 9 Jun 2022 12:00:05 +0200 Subject: [PATCH 086/218] fixing pegasus conventions --- src/lattice.jl | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 3c042e9..d148292 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -1,4 +1,4 @@ -export super_square_lattice, pegasus_lattice +export super_square_lattice, pegasus_lattice, pegasus_lattice_flip12 "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) @@ -18,10 +18,11 @@ function pegasus_lattice(size::NTuple{3, Int}) m, n, t = size # t is number of chimera units old = LinearIndices((1:8*t, 1:n, 1:m)) map = Dict( - old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 1:4) + old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4) ) - for i=1:m, j=1:n, k ∈ (n * 8 + m for n ∈ 0:t-1, m ∈ 5:8) + for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 5:8) push!(map, old[k, j, i] => (i, j, 2)) end map end + From 525d242ec09d943e92a30072ae7fa6028beef3cc Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Tue, 14 Jun 2022 19:29:26 +0200 Subject: [PATCH 087/218] begin writing tests for numbering functions --- test/instances/pegasus/P16.txt | 43992 +++++++++++++++++++++++++++++++ test/instances/pegasus/P2.txt | 117 + test/instances/pegasus/P4.txt | 1541 ++ test/instances/pegasus/P8.txt | 9285 +++++++ test/numeration.jl | 29 + 5 files changed, 54964 insertions(+) create mode 100644 test/instances/pegasus/P16.txt create mode 100644 test/instances/pegasus/P2.txt create mode 100644 test/instances/pegasus/P4.txt create mode 100644 test/instances/pegasus/P8.txt create mode 100644 test/numeration.jl diff --git a/test/instances/pegasus/P16.txt b/test/instances/pegasus/P16.txt new file mode 100644 index 0000000..0220224 --- /dev/null +++ b/test/instances/pegasus/P16.txt @@ -0,0 +1,43992 @@ +# +1 1 -0.0280004116674961 +2 2 3.1519611823144515 +3 3 3.951805308303963 +4 4 0.9785957343134948 +5 5 2.3606441952420303 +6 6 3.5456356068352166 +7 7 -1.9616580433239448 +8 8 3.5100012778338643 +9 9 3.07583544899207 +10 10 2.005631806466014 +11 11 -3.4228832673271583 +12 12 1.2584951413933885 +13 13 1.9408836852725295 +14 14 3.904411722202357 +15 15 1.9332287920911808 +16 16 1.1506894733280555 +17 17 2.277360972286692 +18 18 -2.53431092729718 +19 19 -2.0046436033791943 +20 20 -1.0645184631702789 +21 21 0.648639990744357 +22 22 -0.8465060228203285 +23 23 -2.012585209594944 +24 24 2.670976038532217 +25 25 -3.440257832005856 +26 26 1.9816336947728308 +27 27 -3.921589059020782 +28 28 3.9089492798155296 +29 29 -2.7096216309900534 +30 30 -2.780662628225357 +31 31 1.4034257708537634 +32 32 -1.3035205554478697 +33 33 -0.3711032127864389 +34 34 -3.0105994132408807 +35 35 -1.2979148204536155 +36 36 1.6302960889429243 +37 37 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b/test/numeration.jl @@ -0,0 +1,29 @@ +using NaturalSort + +@testset verbose = true "Numeration generate correct diagonals" begin + + size = [2, 4, 8, 16] + + @testset "$i" for (i, instance) ∈ enumerate(sort(readdir("$(@__DIR__)/instances/pegasus/", join=false), lt = natural)) + println(size[i]) + println(instance) + + + #=instance = "$(@__DIR__)/instances/pegasus/001.txt" + m, n, t = 3, 3, 24 + max_cl_states = 2^2 + + ig = ising_graph(instance) + fg = factor_graph( + ig, + max_cl_states, + spectrum = brute_force, # to use CPU + cluster_assignment_rule=super_square_lattice((m, n, t)) + ) + + for edge in edges(fg) + println(edge) + end + =# + end +end \ No newline at end of file From 99e1d6a09436f1605b4fdae9f1ef502769703a00 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Wed, 15 Jun 2022 00:20:24 +0200 Subject: [PATCH 088/218] begun rewriting code wrom python --- src/SpinGlassNetworks.jl | 1 + src/numeration.jl | 83 ++++++++++++++++++++++++++++++++++++++++ 2 files changed, 84 insertions(+) create mode 100644 src/numeration.jl diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 8106a92..1bac8b6 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -88,4 +88,5 @@ module SpinGlassNetworks include("spectrum.jl") include("lattice.jl") include("factor.jl") + include("numeration.jl") end # module diff --git a/src/numeration.jl b/src/numeration.jl new file mode 100644 index 0000000..48c60a7 --- /dev/null +++ b/src/numeration.jl @@ -0,0 +1,83 @@ +using LabelledGraphs + +export + linear_to_pegasus, + pegasus_to_nice, + linear_to_nice, + droplets_to_pegasus_nice + + +const Instance = Union{String, Dict} +const IsingGraph = LabelledGraph{MetaGraph{Int64, Float64}, Int64} + +""" +Rewriten from Dwave-networkx +""" +function linear_to_pegasus(size::Int, r::Int) + m, m1 = size, size - 1 + r, z = divrem(r, m1) + r, k = divrem(r, 12) + u, w = divrem(r, m) + (u, w, k, z) +end + +""" +Rewriten from Dwave-networkx +""" +function pegasus_to_nice(p::NTuple{4, Int64}) #TODO: Write it better. Now it is rewriten verbatim. + u, w, k, z = p + + t = (2-u-(2*u-1)*floor(k/4)) % 3 + #Python has this weir bechavior that x%y is always nonnegative + if t < 0 + t = t+3 + end + + if t == 0 + if u > 0 + y = w-1 + x = z + else + y = z + x = w + end + + return (round(Int, t), y, x, u, k-4) + + elseif t == 1 + if u > 0 + y = w-1 + x = z + k1 = k + else + y = z + x = w + k1 = k-8 + end + return (round(Int, t), y, x, u, k1) + + elseif t == 2 + if u > 0 + y = w + x = z + k1 = k-8 + else + y = z + x = w-1 + k1 = k + end + return (round(Int, t), y, x, u, k1) + end +end + +function linear_to_nice(size::Int, r::Int) + pegasus_to_nice(linear_to_pegasus(size, r)) +end + +function droplets_to_pegasus_nice(instance::Instance) + ig = ising_graph(instance) + + h_tuple = Dict() + +end + From d2d081007b4c0322e089291ec7d08998f4b40525 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Wed, 15 Jun 2022 00:22:41 +0200 Subject: [PATCH 089/218] tests for written functions --- test/instances/pegasus/2x2x3.txt | 583 +++++++++++++++++++++++++++++++ test/numeration.jl | 90 ++++- test/runtests.jl | 2 +- 3 files changed, 659 insertions(+), 16 deletions(-) create mode 100644 test/instances/pegasus/2x2x3.txt diff --git a/test/instances/pegasus/2x2x3.txt b/test/instances/pegasus/2x2x3.txt new file mode 100644 index 0000000..ff853a5 --- /dev/null +++ b/test/instances/pegasus/2x2x3.txt @@ -0,0 +1,583 @@ +# +1 1 0.031250 +2 2 0.031250 +3 3 -0.031250 +4 4 -0.031250 +5 5 -0.062500 +6 6 0.031250 +8 8 0.031250 +9 9 0.062500 +10 10 0.031250 +11 11 -0.062500 +12 12 -0.062500 +14 14 -0.062500 +16 16 -0.062500 +17 17 -0.031250 +18 18 -0.062500 +19 19 0.031250 +20 20 -0.031250 +22 22 0.031250 +23 23 -0.031250 +24 24 0.031250 +25 25 0.031250 +26 26 0.031250 +28 28 -0.031250 +29 29 -0.062500 +30 30 -0.062500 +32 32 -0.062500 +33 33 0.062500 +34 34 0.062500 +35 35 -0.031250 +36 36 0.031250 +38 38 0.031250 +39 39 0.031250 +40 40 0.062500 +42 42 0.062500 +43 43 0.031250 +44 44 0.062500 +46 46 0.031250 +47 47 -0.031250 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b/test/numeration.jl index 933a154..8a4337a 100644 --- a/test/numeration.jl +++ b/test/numeration.jl @@ -1,29 +1,89 @@ -using NaturalSort -@testset verbose = true "Numeration generate correct diagonals" begin +# It is posible that more thorough tests will be needed - size = [2, 4, 8, 16] +@testset verbose = true "Renumeration works like in python" begin + #instance = "$(@__DIR__)/instances/pegasus/2x2x3.txt" - @testset "$i" for (i, instance) ∈ enumerate(sort(readdir("$(@__DIR__)/instances/pegasus/", join=false), lt = natural)) - println(size[i]) - println(instance) + @testset "linear_to_pegasus" begin + python_P2_ltp = Dict(0 => (0, 0, 0, 0), 11 => (0, 0, 11, 0), + 18 => (0, 1, 6, 0), 23 => (0, 1, 11, 0)) - #=instance = "$(@__DIR__)/instances/pegasus/001.txt" - m, n, t = 3, 3, 24 - max_cl_states = 2^2 + python_P4_ltp = Dict(0 => (0, 0, 0, 0), 86 => (0, 2, 4, 2), + 112 => (0, 3, 1, 1), 215 => (1, 1, 11, 2)) - ig = ising_graph(instance) + python_P8_ltp = Dict(0 => (0, 0, 0, 0), 253 => (0, 3, 0, 1), + 860 => (1, 2, 2, 6), 1175=> (1, 5, 11, 6)) + + python_P16_ltp = Dict(0 => (0, 0, 0, 0), 2530 => (0, 14, 0, 10), + 4860 => (1, 11, 0, 0), 5399 => (1, 13, 11, 14)) + + for i in keys(python_P2_ltp) + @test linear_to_pegasus(2, i) == python_P2_ltp[i] + end + + for i in keys(python_P4_ltp) + @test linear_to_pegasus(4, i) == python_P4_ltp[i] + end + + for i in keys(python_P8_ltp) + @test linear_to_pegasus(8, i) == python_P8_ltp[i] + end + + for i in keys(python_P16_ltp) + @test linear_to_pegasus(16, i) == python_P16_ltp[i] + end + end + + @testset "pegasus_to_nice" begin + + python_ptn = Dict((0,0,4,0) => (0, 0, 0, 0, 0), (0, 3, 1, 1) => (2, 1, 2, 0, 1), + (1, 5, 11, 6) => (2, 5, 6, 1, 3), (1, 14, 0, 10) => (1, 13, 10, 1, 0)) + + for p in keys(python_ptn) + @test pegasus_to_nice(p) == python_ptn[p] + end + end + + @testset "linear_to_nice" begin + @test linear_to_nice(16, 111) == (0, 6, 0, 0, 3) + end + + +end + +# This test takes long time. + +@testset verbose = true "Renumerated instances generate correct factor graph" begin + instance_dir = "$(@__DIR__)/instances/pegasus/" + instances = ["P2", "P4", "P8", "P16"] + size = [2,4,8,16] + + @testset "$instance" for (i, instance) ∈ enumerate(instances) + + instance = instance * ".txt" + s = size[i]-1 + m, n, t = s, s, 24 + max_cl_states = 2 + + ig = ising_graph(joinpath(instance_dir, instance)) fg = factor_graph( ig, max_cl_states, - spectrum = brute_force, # to use CPU + spectrum = brute_force, cluster_assignment_rule=super_square_lattice((m, n, t)) ) + + @test nv(fg) == s^2 - for edge in edges(fg) - println(edge) + if s > 1 + for l in 1:s-1, k in 2:s + @test has_edge(fg, (l,k), (l+1,k-1)) + end end - =# + + end -end \ No newline at end of file +end + + diff --git a/test/runtests.jl b/test/runtests.jl index 32eea43..c11af6f 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -26,7 +26,7 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) eng end -my_tests = ["ising.jl", "factor.jl"] +my_tests = ["numeration.jl",]#["ising.jl", "factor.jl"] for my_test ∈ my_tests include(my_test) From dd8c976d9c6c9f4e352a90283c5cbc917b02842c Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Wed, 15 Jun 2022 11:20:34 +0200 Subject: [PATCH 090/218] all main functions for numerate --- src/numeration.jl | 24 ++++++++++++++++++++++-- test/numeration.jl | 10 ++++++++++ 2 files changed, 32 insertions(+), 2 deletions(-) diff --git a/src/numeration.jl b/src/numeration.jl index 48c60a7..093287a 100644 --- a/src/numeration.jl +++ b/src/numeration.jl @@ -4,11 +4,13 @@ export linear_to_pegasus, pegasus_to_nice, linear_to_nice, + nice_to_dattani, + dattani_to_linear, droplets_to_pegasus_nice const Instance = Union{String, Dict} -const IsingGraph = LabelledGraph{MetaGraph{Int64, Float64}, Int64} + """ Rewriten from Dwave-networkx @@ -24,7 +26,7 @@ end """ Rewriten from Dwave-networkx """ -function pegasus_to_nice(p::NTuple{4, Int64}) #TODO: Write it better. Now it is rewriten verbatim. +function pegasus_to_nice(p::NTuple{4, Int}) #TODO: Write it better. Now it is rewriten verbatim. u, w, k, z = p t = (2-u-(2*u-1)*floor(k/4)) % 3 @@ -70,10 +72,14 @@ function pegasus_to_nice(p::NTuple{4, Int64}) #TODO: Write it better. Now it is end end +""" +Rewriten from Dwave-networkx +""" function linear_to_nice(size::Int, r::Int) pegasus_to_nice(linear_to_pegasus(size, r)) end + function droplets_to_pegasus_nice(instance::Instance) ig = ising_graph(instance) @@ -81,3 +87,17 @@ function droplets_to_pegasus_nice(instance::Instance) end +""" +Changes pegasus_nice tuple into tuple from Dattani's paper. +It is worth noting that two last indexes in Dattani's paper corespond to binary representatation of number from [0,1,2,3] +""" +function nice_to_dattani(pn::NTuple{5, Int}) + (pn[3], pn[2], pn[1], pn[4], pn[5]) +end + +""" +Changes tuple into linear index inspired by Dattani's paper +""" +function dattani_to_linear(size::Int, d::NTuple{5, Int}) + 24*(size - 1) * d[1] + 24 * d[2] + 8 * d[3] + 4 * d[4] + d[5] + 1 +end \ No newline at end of file diff --git a/test/numeration.jl b/test/numeration.jl index 8a4337a..9082f96 100644 --- a/test/numeration.jl +++ b/test/numeration.jl @@ -49,7 +49,17 @@ @test linear_to_nice(16, 111) == (0, 6, 0, 0, 3) end + @testset "nice_to_dattani" begin + @test nice_to_dattani((2, 5, 6, 1, 3)) == (6, 5, 2, 1, 3) + end + @testset "dattani_to_linear" begin + python_P16_dtl = Dict((12, 7, 1, 1, 0) => 4501, (6, 10, 1, 0, 0) => 2409, + (3, 2, 2, 0, 1) => 1146, (9, 0, 2, 0, 3)=> 3260, (10, 3, 1, 0, 2) => 3683) + for i in keys(python_P16_dtl) + @test dattani_to_linear(16, i) == python_P16_dtl[i] + end + end end # This test takes long time. From 4229e886744097c69e9a18f41c7c668e802bd81a Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Wed, 15 Jun 2022 13:59:37 +0200 Subject: [PATCH 091/218] add ref --- src/numeration.jl | 46 +++++++++++++++------------------------------- 1 file changed, 15 insertions(+), 31 deletions(-) diff --git a/src/numeration.jl b/src/numeration.jl index 093287a..b96061b 100644 --- a/src/numeration.jl +++ b/src/numeration.jl @@ -1,6 +1,6 @@ using LabelledGraphs -export +export linear_to_pegasus, pegasus_to_nice, linear_to_nice, @@ -8,12 +8,10 @@ export dattani_to_linear, droplets_to_pegasus_nice - const Instance = Union{String, Dict} - """ -Rewriten from Dwave-networkx +Rewriten from Dwave-networkx lib """ function linear_to_pegasus(size::Int, r::Int) m, m1 = size, size - 1 @@ -29,21 +27,17 @@ Rewriten from Dwave-networkx function pegasus_to_nice(p::NTuple{4, Int}) #TODO: Write it better. Now it is rewriten verbatim. u, w, k, z = p - t = (2-u-(2*u-1)*floor(k/4)) % 3 - #Python has this weir bechavior that x%y is always nonnegative - if t < 0 - t = t+3 - end + t = (2 - u - (2 * u - 1) * floor(k / 4)) % 3 + if t < 0 t = t+3 end if t == 0 if u > 0 y = w-1 x = z - else + else y = z x = w end - return (round(Int, t), y, x, u, k-4) elseif t == 1 @@ -51,7 +45,7 @@ function pegasus_to_nice(p::NTuple{4, Int}) #TODO: Write it better. Now it is re y = w-1 x = z k1 = k - else + else y = z x = w k1 = k-8 @@ -63,7 +57,7 @@ function pegasus_to_nice(p::NTuple{4, Int}) #TODO: Write it better. Now it is re y = w x = z k1 = k-8 - else + else y = z x = w-1 k1 = k @@ -75,29 +69,19 @@ end """ Rewriten from Dwave-networkx """ -function linear_to_nice(size::Int, r::Int) - pegasus_to_nice(linear_to_pegasus(size, r)) -end - - -function droplets_to_pegasus_nice(instance::Instance) - ig = ising_graph(instance) - - h_tuple = Dict() - -end +linear_to_nice(size::Int, r::Int) = pegasus_to_nice(linear_to_pegasus(size, r)) """ -Changes pegasus_nice tuple into tuple from Dattani's paper. -It is worth noting that two last indexes in Dattani's paper corespond to binary representatation of number from [0,1,2,3] +Based on [1] https://arxiv.org/abs/1901.07636 +Changes pegasus_nice tuple into tuple from [1]. +It is worth noting that two last indexes in [1] +corespond to binary representatation of number from [0, 1, 2, 3] """ -function nice_to_dattani(pn::NTuple{5, Int}) - (pn[3], pn[2], pn[1], pn[4], pn[5]) -end +nice_to_dattani(pn::NTuple{5, Int}) = (pn[3], pn[2], pn[1], pn[4], pn[5]) """ Changes tuple into linear index inspired by Dattani's paper """ function dattani_to_linear(size::Int, d::NTuple{5, Int}) - 24*(size - 1) * d[1] + 24 * d[2] + 8 * d[3] + 4 * d[4] + d[5] + 1 -end \ No newline at end of file + 24 * (size - 1) * d[1] + 24 * d[2] + 8 * d[3] + 4 * d[4] + d[5] + 1 +end From 993cca8d3bf2007ef41f6844ce7567b788a21ed9 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Wed, 15 Jun 2022 14:59:56 +0200 Subject: [PATCH 092/218] clean up --- test/numeration.jl | 14 +++++--------- 1 file changed, 5 insertions(+), 9 deletions(-) diff --git a/test/numeration.jl b/test/numeration.jl index 9082f96..2c2b4c8 100644 --- a/test/numeration.jl +++ b/test/numeration.jl @@ -6,7 +6,7 @@ @testset "linear_to_pegasus" begin - python_P2_ltp = Dict(0 => (0, 0, 0, 0), 11 => (0, 0, 11, 0), + python_P2_ltp = Dict(0 => (0, 0, 0, 0), 11 => (0, 0, 11, 0), 18 => (0, 1, 6, 0), 23 => (0, 1, 11, 0)) python_P4_ltp = Dict(0 => (0, 0, 0, 0), 86 => (0, 2, 4, 2), @@ -37,7 +37,7 @@ @testset "pegasus_to_nice" begin - python_ptn = Dict((0,0,4,0) => (0, 0, 0, 0, 0), (0, 3, 1, 1) => (2, 1, 2, 0, 1), + python_ptn = Dict((0,0,4,0) => (0, 0, 0, 0, 0), (0, 3, 1, 1) => (2, 1, 2, 0, 1), (1, 5, 11, 6) => (2, 5, 6, 1, 3), (1, 14, 0, 10) => (1, 13, 10, 1, 0)) for p in keys(python_ptn) @@ -54,7 +54,7 @@ end @testset "dattani_to_linear" begin - python_P16_dtl = Dict((12, 7, 1, 1, 0) => 4501, (6, 10, 1, 0, 0) => 2409, + python_P16_dtl = Dict((12, 7, 1, 1, 0) => 4501, (6, 10, 1, 0, 0) => 2409, (3, 2, 2, 0, 1) => 1146, (9, 0, 2, 0, 3)=> 3260, (10, 3, 1, 0, 2) => 3683) for i in keys(python_P16_dtl) @test dattani_to_linear(16, i) == python_P16_dtl[i] @@ -80,10 +80,10 @@ end fg = factor_graph( ig, max_cl_states, - spectrum = brute_force, + spectrum = brute_force, cluster_assignment_rule=super_square_lattice((m, n, t)) ) - + @test nv(fg) == s^2 if s > 1 @@ -91,9 +91,5 @@ end @test has_edge(fg, (l,k), (l+1,k-1)) end end - - end end - - From ee626869f5a6f4ccc79d84132fd0dfaff5e51bc1 Mon Sep 17 00:00:00 2001 From: bartekGardas Date: Tue, 21 Jun 2022 15:28:14 +0200 Subject: [PATCH 093/218] clean up --- src/SpinGlassNetworks.jl | 2 +- src/factor.jl | 10 ++++++++-- src/lattice.jl | 6 ++++-- src/spectrum.jl | 12 ++++++++++-- src/{numeration.jl => utils.jl} | 0 test/runtests.jl | 6 +++++- test/{numeration.jl => utils.jl} | 0 7 files changed, 28 insertions(+), 8 deletions(-) rename src/{numeration.jl => utils.jl} (100%) rename test/{numeration.jl => utils.jl} (100%) diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 1bac8b6..0a0f097 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -88,5 +88,5 @@ module SpinGlassNetworks include("spectrum.jl") include("lattice.jl") include("factor.jl") - include("numeration.jl") + include("utils.jl") end # module diff --git a/src/factor.jl b/src/factor.jl index fdd2c81..5459199 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -1,5 +1,11 @@ -export factor_graph, rank_reveal, projectors, split_into_clusters -export decode_factor_graph_state, energy, cluster_size +export + factor_graph, + rank_reveal, + projectors, + split_into_clusters, + decode_factor_graph_state, + energy, + cluster_size """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) diff --git a/src/lattice.jl b/src/lattice.jl index d148292..7bc682d 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -1,4 +1,7 @@ -export super_square_lattice, pegasus_lattice, pegasus_lattice_flip12 +export + super_square_lattice, + pegasus_lattice, + pegasus_lattice_flip12 "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) @@ -25,4 +28,3 @@ function pegasus_lattice(size::NTuple{3, Int}) end map end - diff --git a/src/spectrum.jl b/src/spectrum.jl index 67e6c4b..b06d520 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -1,5 +1,13 @@ -export all_states, local_basis, gibbs_tensor, brute_force -export full_spectrum, Spectrum, idx, local_basis, energy +export + all_states, + local_basis, + gibbs_tensor, + brute_force, + full_spectrum, + Spectrum, + idx, + local_basis, + energy @inline idx(σ::Int) = (σ == -1) ? 1 : σ + 1 @inline local_basis(d::Int) = union(-1, 1:d-1) diff --git a/src/numeration.jl b/src/utils.jl similarity index 100% rename from src/numeration.jl rename to src/utils.jl diff --git a/test/runtests.jl b/test/runtests.jl index c11af6f..a31f9f2 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -26,7 +26,11 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) eng end -my_tests = ["numeration.jl",]#["ising.jl", "factor.jl"] +my_tests = [ + "ising.jl", + "factor.jl", + "utils.jl", +] for my_test ∈ my_tests include(my_test) diff --git a/test/numeration.jl b/test/utils.jl similarity index 100% rename from test/numeration.jl rename to test/utils.jl From 1e93bdc29d5c99ed97837f99c15aaef330fa7ff9 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 29 Jun 2022 15:01:17 +0200 Subject: [PATCH 094/218] add pegasus_lattice_masoud --- src/lattice.jl | 16 ++++++++++++++-- 1 file changed, 14 insertions(+), 2 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 7bc682d..c99e4e6 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -1,8 +1,8 @@ export super_square_lattice, pegasus_lattice, - pegasus_lattice_flip12 - + pegasus_lattice_masoud + "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) m, um, n, un, t = size @@ -28,3 +28,15 @@ function pegasus_lattice(size::NTuple{3, Int}) end map end + +function pegasus_lattice_masoud(size::NTuple{3, Int}) + m, n, t = size # t is number of chimera units + old = LinearIndices((1:8*t, 1:n, 1:m)) + map = Dict( + old[k, j, i] => (i, j, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4) + ) + for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 5:8) + push!(map, old[k, j, i] => (i, j, 1)) + end + map +end From 2c3d626ffa0bbdd8a33c4238e764ce482c461609 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 30 Jun 2022 14:40:55 +0200 Subject: [PATCH 095/218] add pegasus_lattice_tomek --- src/lattice.jl | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/src/lattice.jl b/src/lattice.jl index c99e4e6..862bfe6 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -1,7 +1,9 @@ export super_square_lattice, pegasus_lattice, - pegasus_lattice_masoud + pegasus_lattice_masoud, + pegasus_lattice_tomek, + zephyr_lattice "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) @@ -40,3 +42,15 @@ function pegasus_lattice_masoud(size::NTuple{3, Int}) end map end + +function pegasus_lattice_tomek(size::NTuple{3, Int}) + m, n, t = size # t is number of chimera units + old = LinearIndices((1:8*t, 1:n, 1:m)) + map = Dict( + old[k, j, i] => (i, n-j+1, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4) + ) + for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 5:8) + push!(map, old[k, j, i] => (i, n-j+1, 1)) + end + map +end \ No newline at end of file From 4d70c3e41499bb84f98a589b3058a4ea1cc2df32 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Fri, 1 Jul 2022 15:55:49 +0200 Subject: [PATCH 096/218] early work on zephyr lattice --- src/lattice.jl | 19 ++++++++++++++++++- 1 file changed, 18 insertions(+), 1 deletion(-) diff --git a/src/lattice.jl b/src/lattice.jl index 862bfe6..0bb5756 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -53,4 +53,21 @@ function pegasus_lattice_tomek(size::NTuple{3, Int}) push!(map, old[k, j, i] => (i, n-j+1, 1)) end map -end \ No newline at end of file +end + +#= +function zephyr_lattice(size::NTuple{3, Int}) +m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) +map = Dict() +# odd columns +for i=1:2:2*m+1, j=1:n + for p in 1:2*t + push!(map, (i-1)*(2*n*t) + (p-1)*n + (j-1) => (i,j,1)) + end +end +#even columns + for i=0:2:2*m, j=1:n+1 + + end +end +=# \ No newline at end of file From 5be4fcf9a3a0c187d8ef0e5bfbb7b8fc70c0b87a Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Tue, 5 Jul 2022 14:43:00 +0200 Subject: [PATCH 097/218] zephyr lattice (Z1) --- src/lattice.jl | 38 ++++++++++++++++++++++++++++---------- 1 file changed, 28 insertions(+), 10 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 0bb5756..7697683 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -55,19 +55,37 @@ function pegasus_lattice_tomek(size::NTuple{3, Int}) map end -#= -function zephyr_lattice(size::NTuple{3, Int}) + +function zephyr_lattice(size::NTuple{3, Int})::Dict{Int, NTuple{3, Int}} m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) map = Dict() -# odd columns -for i=1:2:2*m+1, j=1:n - for p in 1:2*t - push!(map, (i-1)*(2*n*t) + (p-1)*n + (j-1) => (i,j,1)) + +for i=1:2*n, j=1:2*m + for p in p_func(i, j, t) + push!(map, (i-1)*(2*n*t) + (j-1)*(2*m*t) + p*n + (i-1)*(j%2) => (i,j,1)) + end + + for q in q_func(i, j, t) + push!(map, 2*t*(2*n+1) + (i-1)*(2*n*t) + (j%2)*(2*m*t) + q*m + (j-1)*(i-1) => (i,j,2)) end + +end +map end -#even columns - for i=0:2:2*m, j=1:n+1 - end +function flag_horizontal(i::Int, j::Int) + (i+j)%2 == 1 ? true : false +end + +function flag_vertical(i::Int, j::Int) + (i+j)%2 == 0 ? true : false +end + + +function p_func(i::Int, j::Int, t::Int) + flag_horizontal(i, j) ? collect(1:2:2*t) : collect(1:2*t) +end + +function q_func(i::Int, j::Int, t::Int) + flag_vertical(i, j) ? collect(1:2:2*t) : collect(1:2*t) end -=# \ No newline at end of file From 34b75a05b6991819846e841013ee62ede5df9231 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Thu, 7 Jul 2022 15:26:04 +0200 Subject: [PATCH 098/218] started work on zephyr lattice boundary --- src/lattice.jl | 40 ++++++++++++++++++++++++++++++++++------ 1 file changed, 34 insertions(+), 6 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 7697683..e24b158 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -3,7 +3,8 @@ export pegasus_lattice, pegasus_lattice_masoud, pegasus_lattice_tomek, - zephyr_lattice + zephyr_lattice, + j_function "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) @@ -56,11 +57,11 @@ function pegasus_lattice_tomek(size::NTuple{3, Int}) end -function zephyr_lattice(size::NTuple{3, Int})::Dict{Int, NTuple{3, Int}} +function zephyr_lattice_z1(size::NTuple{3, Int}) m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) -map = Dict() +map = Dict{Int, NTuple{3, Int}}() -for i=1:2*n, j=1:2*m +for i=1:2*n, j in 1:2*m for p in p_func(i, j, t) push!(map, (i-1)*(2*n*t) + (j-1)*(2*m*t) + p*n + (i-1)*(j%2) => (i,j,1)) end @@ -73,12 +74,31 @@ end map end + +function zephyr_lattice_boundary(size::NTuple{3, Int}) + m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) + map = Dict{Int, NTuple{3, Int}}() + + for i=1:2*n, j in j_function(i, n) + for p in p_func(i, j, t) + push!(map, p*n + i%n => (i,j,1)) + end + + for q in q_func(i, j, t) + push!(map, q*m => (i,j,2)) + end + + end + map + end + + function flag_horizontal(i::Int, j::Int) - (i+j)%2 == 1 ? true : false + (i ∈ 1:n && j ∈ (m + 1):2*m) || (i ∈ (n+1): 2*n && j ∈ 1:m) ? true : false end function flag_vertical(i::Int, j::Int) - (i+j)%2 == 0 ? true : false + (i ∈ 1:n && j ∈ 1:m) || (i ∈ (n+1): 2*n && j ∈ (m + 1):2*m) ? true : false end @@ -89,3 +109,11 @@ end function q_func(i::Int, j::Int, t::Int) flag_vertical(i, j) ? collect(1:2:2*t) : collect(1:2*t) end + +function j_function(i::Int, n::Int) + if i in collect(1:n) + return collect((n + 1 - i):(n + i)) + else + return collect((i-n):(3*n + 1 - i)) + end +end From ecc343bc571593743cc00a05f2b310cd7c024a37 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 7 Jul 2022 20:28:22 +0200 Subject: [PATCH 099/218] clean up Z1 --- src/lattice.jl | 39 ++++++++++++++++++++------------------- 1 file changed, 20 insertions(+), 19 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index e24b158..0abedfc 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -4,6 +4,7 @@ export pegasus_lattice_masoud, pegasus_lattice_tomek, zephyr_lattice, + zephyr_lattice_z1, j_function "Variable number of Ising graph -> Factor graph coordinate system" @@ -58,20 +59,20 @@ end function zephyr_lattice_z1(size::NTuple{3, Int}) -m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) -map = Dict{Int, NTuple{3, Int}}() + m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) + map = Dict{Int, NTuple{3, Int}}() -for i=1:2*n, j in 1:2*m - for p in p_func(i, j, t) - push!(map, (i-1)*(2*n*t) + (j-1)*(2*m*t) + p*n + (i-1)*(j%2) => (i,j,1)) - end + for i=1:2*n, j in 1:2*m + for p in p_func(i, j, t, n, m) + push!(map, (i-1)*(2*n*t) + (j-1)*(2*m*t) + p*n + (i-1)*(j%2) => (i,j,1)) + end + + for q in q_func(i, j, t, n, m) + push!(map, 2*t*(2*n+1) + (i-1)*(2*n*t) + (j%2)*(2*m*t) + q*m + (j-1)*(i-1) => (i,j,2)) + end - for q in q_func(i, j, t) - push!(map, 2*t*(2*n+1) + (i-1)*(2*n*t) + (j%2)*(2*m*t) + q*m + (j-1)*(i-1) => (i,j,2)) end - -end -map + map end @@ -80,11 +81,11 @@ function zephyr_lattice_boundary(size::NTuple{3, Int}) map = Dict{Int, NTuple{3, Int}}() for i=1:2*n, j in j_function(i, n) - for p in p_func(i, j, t) + for p in p_func(i, j, t, n, m) push!(map, p*n + i%n => (i,j,1)) end - for q in q_func(i, j, t) + for q in q_func(i, j, t, n, m) push!(map, q*m => (i,j,2)) end @@ -93,21 +94,21 @@ function zephyr_lattice_boundary(size::NTuple{3, Int}) end -function flag_horizontal(i::Int, j::Int) +function flag_horizontal(i::Int, j::Int, n::Int, m::Int) (i ∈ 1:n && j ∈ (m + 1):2*m) || (i ∈ (n+1): 2*n && j ∈ 1:m) ? true : false end -function flag_vertical(i::Int, j::Int) +function flag_vertical(i::Int, j::Int, n::Int, m::Int) (i ∈ 1:n && j ∈ 1:m) || (i ∈ (n+1): 2*n && j ∈ (m + 1):2*m) ? true : false end -function p_func(i::Int, j::Int, t::Int) - flag_horizontal(i, j) ? collect(1:2:2*t) : collect(1:2*t) +function p_func(i::Int, j::Int, t::Int, n::Int, m::Int) + flag_horizontal(i, j, n, m) ? collect(1:2:2*t) : collect(1:2*t) end -function q_func(i::Int, j::Int, t::Int) - flag_vertical(i, j) ? collect(1:2:2*t) : collect(1:2*t) +function q_func(i::Int, j::Int, t::Int, n::Int, m::Int) + flag_vertical(i, j, n, m) ? collect(1:2:2*t) : collect(1:2*t) end function j_function(i::Int, n::Int) From 368365186816cb1a901c875d88a40590a4d13b3a Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Mon, 11 Jul 2022 15:19:44 +0200 Subject: [PATCH 100/218] horizontal spins in zephyr --- src/lattice.jl | 34 +++++++++++++++++++++++++--------- 1 file changed, 25 insertions(+), 9 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 0abedfc..670fc0e 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -64,11 +64,11 @@ function zephyr_lattice_z1(size::NTuple{3, Int}) for i=1:2*n, j in 1:2*m for p in p_func(i, j, t, n, m) - push!(map, (i-1)*(2*n*t) + (j-1)*(2*m*t) + p*n + (i-1)*(j%2) => (i,j,1)) + push!(map, (i-1)*(2*n*t) + (j-1)*(2*m*t) + p*n + (i-1)*(j%2) + 1 => (i,j,1)) end for q in q_func(i, j, t, n, m) - push!(map, 2*t*(2*n+1) + (i-1)*(2*n*t) + (j%2)*(2*m*t) + q*m + (j-1)*(i-1) => (i,j,2)) + push!(map, 2*t*(2*n+1) + (i-1)*(2*n*t) + (j%2)*(2*m*t) + q*m + (j-1)*(i-1) + 1 => (i,j,2)) end end @@ -80,13 +80,13 @@ function zephyr_lattice_boundary(size::NTuple{3, Int}) m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) map = Dict{Int, NTuple{3, Int}}() - for i=1:2*n, j in j_function(i, n) + for i=1:2*n, j in [j_function(i, n)[begin], j_function(i, n)[end]] for p in p_func(i, j, t, n, m) - push!(map, p*n + i%n => (i,j,1)) + push!(map, (i-1)*(2*n*t) + p*n + (j-m)*2m*t + max(0, i-j) + Int(flag_down(i, j, n, m))*(n-1) + 1 => (i,j,1)) end for q in q_func(i, j, t, n, m) - push!(map, q*m => (i,j,2)) + push!(map, 2*n*t*(2*n+1) + q*m + 1 => (i,j,2)) end end @@ -94,21 +94,37 @@ function zephyr_lattice_boundary(size::NTuple{3, Int}) end +function flag_left(i::Int, j::Int, n::Int, m::Int) + (i ∈ 1:n && j == m - i + 1) ? true : false +end + +function flag_right(i::Int, j::Int, n::Int, m::Int) + (i ∈ n+1:2*n && j == 3*m + 1 - i) ? true : false +end + +function flag_up(i::Int, j::Int, n::Int, m::Int) + (i == j-n && j ∈ m + 1:2*m ) ? true : false +end + +function flag_down(i::Int, j::Int, n::Int, m::Int) + (i == j + n && j ∈ 1:m ) ? true : false +end + function flag_horizontal(i::Int, j::Int, n::Int, m::Int) - (i ∈ 1:n && j ∈ (m + 1):2*m) || (i ∈ (n+1): 2*n && j ∈ 1:m) ? true : false + flag_down(i, j, n, m) || flag_up(i, j, n, m) ? true : false end function flag_vertical(i::Int, j::Int, n::Int, m::Int) - (i ∈ 1:n && j ∈ 1:m) || (i ∈ (n+1): 2*n && j ∈ (m + 1):2*m) ? true : false + flag_left(i, j, n, m) || flag_right(i, j, n, m) ? true : false end function p_func(i::Int, j::Int, t::Int, n::Int, m::Int) - flag_horizontal(i, j, n, m) ? collect(1:2:2*t) : collect(1:2*t) + flag_horizontal(i, j, n, m) ? collect(0:2:2*t-1) : collect(0:2*t-1) end function q_func(i::Int, j::Int, t::Int, n::Int, m::Int) - flag_vertical(i, j, n, m) ? collect(1:2:2*t) : collect(1:2*t) + flag_vertical(i, j, n, m) ? collect(0:2:2*t-1) : collect(0:2*t-1) end function j_function(i::Int, n::Int) From 4eda736c9b4fe82659d5a877c823368d95e32215 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Tue, 12 Jul 2022 12:46:28 +0200 Subject: [PATCH 101/218] zephyr_to_linear, linear_to_zephy --- src/utils.jl | 36 +++++++++++++++++++++++++++++++++++- 1 file changed, 35 insertions(+), 1 deletion(-) diff --git a/src/utils.jl b/src/utils.jl index b96061b..b3c8b47 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -6,8 +6,11 @@ export linear_to_nice, nice_to_dattani, dattani_to_linear, - droplets_to_pegasus_nice + droplets_to_pegasus_nice, + linear_to_zephyr, + zephyr_to_linear + const Instance = Union{String, Dict} """ @@ -85,3 +88,34 @@ Changes tuple into linear index inspired by Dattani's paper function dattani_to_linear(size::Int, d::NTuple{5, Int}) 24 * (size - 1) * d[1] + 24 * d[2] + 8 * d[3] + 4 * d[4] + d[5] + 1 end + +""" +Rewriten from Dwave-networkx +""" +function linear_to_zephyr(m::Int, t::Int, ind::Int) + # m - Grid parameter for the Zephyr lattice. + # t - Tile parameter for the Zephyr lattice; must be even. + + M = 2 * m + 1 + + ind, z = divrem(ind, m) + ind, j = divrem(ind, 2) + ind, k = divrem(ind, t) + u, w = divrem(ind, M) + + (u, w, k, j, z) +end + +""" +Rewriten from Dwave-networkx +""" +function zephyr_to_linear(m::Int, t::Int, q::NTuple{5, Int}) + # m - Grid parameter for the Zephyr lattice. + # t - Tile parameter for the Zephyr lattice; must be even. + + M = 2 * m + 1 + u, w, k, j, z = q + ind = (((u * M + w) * t + k) * 2 + j) * m + z + + ind +end \ No newline at end of file From 0a21d70a1b0e358f9490e578baba8fd0a55e4d97 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Tue, 12 Jul 2022 12:46:48 +0200 Subject: [PATCH 102/218] started work on lattice_5_tuple --- src/lattice.jl | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/src/lattice.jl b/src/lattice.jl index 670fc0e..5d7f823 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -134,3 +134,14 @@ function j_function(i::Int, n::Int) return collect((i-n):(3*n + 1 - i)) end end + +function zephyr_lattice_z1_5tuple(size::NTuple{3, Int}) + m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) + map = Dict{Int, NTuple{3, Int}}() + + # ( u, w, k, ζ, z) + + for u ∈ 0:1, w ∈ 0:2*m, k ∈ 0:t-1, ζ ∈ 0:1, z ∈ 0:n-1 + push!(map, zephyr_to_linear(m, t, ()) => (i, j, u + 1)) + end +end \ No newline at end of file From fac107777c95dd77354a5ab1cc6f9abf322a8ebe Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 14 Jul 2022 12:27:00 +0200 Subject: [PATCH 103/218] zephyr lattice Z2 square --- src/lattice.jl | 24 +++++++++++++++++++++--- 1 file changed, 21 insertions(+), 3 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 5d7f823..fe4bb35 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -5,7 +5,8 @@ export pegasus_lattice_tomek, zephyr_lattice, zephyr_lattice_z1, - j_function + j_function, + zephyr_lattice_z1_5tuple "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) @@ -141,7 +142,24 @@ function zephyr_lattice_z1_5tuple(size::NTuple{3, Int}) # ( u, w, k, ζ, z) - for u ∈ 0:1, w ∈ 0:2*m, k ∈ 0:t-1, ζ ∈ 0:1, z ∈ 0:n-1 - push!(map, zephyr_to_linear(m, t, ()) => (i, j, u + 1)) + for u = 0 + for w ∈ 0:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, (i,z) ∈ enumerate(0:n-1) + push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (2*i, w + 1, 1)) + end + for w ∈ 1:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, z ∈ 0:n-1 + push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (2*z + 2*ζ + 1, w + 1, 1)) + end end + + for u = 1 + for w ∈ 0:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, (i,z) ∈ enumerate(0:n-1) + push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (w + 1, 2*i, 2)) + end + for w ∈ 0:2*m, k ∈ 0:t-1, ζ ∈ 0:1, z ∈ 0:n-1 + push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (w + 1, 2*z + 2*ζ + u, 2)) + end + end + + map + end \ No newline at end of file From 4a98da6fb75a9f9a490f9f1fb51aa5f277dfe9a2 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 14 Jul 2022 17:07:50 +0200 Subject: [PATCH 104/218] fix bug --- src/lattice.jl | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index fe4bb35..e715a58 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -6,7 +6,7 @@ export zephyr_lattice, zephyr_lattice_z1, j_function, - zephyr_lattice_z1_5tuple + zephyr_lattice_5tuple "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) @@ -136,7 +136,7 @@ function j_function(i::Int, n::Int) end end -function zephyr_lattice_z1_5tuple(size::NTuple{3, Int}) +function zephyr_lattice_5tuple(size::NTuple{3, Int}) m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) map = Dict{Int, NTuple{3, Int}}() @@ -155,11 +155,10 @@ function zephyr_lattice_z1_5tuple(size::NTuple{3, Int}) for w ∈ 0:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, (i,z) ∈ enumerate(0:n-1) push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (w + 1, 2*i, 2)) end - for w ∈ 0:2*m, k ∈ 0:t-1, ζ ∈ 0:1, z ∈ 0:n-1 + for w ∈ 1:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, z ∈ 0:n-1 push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (w + 1, 2*z + 2*ζ + u, 2)) end end - map end \ No newline at end of file From ee3e168171dbdf8e5a8cba32c3f46d3812dc1765 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 14 Jul 2022 20:54:59 +0200 Subject: [PATCH 105/218] zephyr lattice rotated works for z1 and z2 --- src/lattice.jl | 39 ++++++++++++++++++++++++++++++++++----- src/utils.jl | 2 +- 2 files changed, 35 insertions(+), 6 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index e715a58..372f33c 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -6,7 +6,8 @@ export zephyr_lattice, zephyr_lattice_z1, j_function, - zephyr_lattice_5tuple + zephyr_lattice_5tuple, + zephyr_lattice_5tuple_rotated "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) @@ -144,21 +145,49 @@ function zephyr_lattice_5tuple(size::NTuple{3, Int}) for u = 0 for w ∈ 0:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, (i,z) ∈ enumerate(0:n-1) - push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (2*i, w + 1, 1)) + push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) => (2*i, w + 1, 1)) end for w ∈ 1:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, z ∈ 0:n-1 - push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (2*z + 2*ζ + 1, w + 1, 1)) + push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) => (2*z + 2*ζ + 1, w + 1, 1)) end end for u = 1 for w ∈ 0:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, (i,z) ∈ enumerate(0:n-1) - push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (w + 1, 2*i, 2)) + push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) => (w + 1, 2*i, 2)) end for w ∈ 1:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, z ∈ 0:n-1 - push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) + 1 => (w + 1, 2*z + 2*ζ + u, 2)) + push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) => (w + 1, 2*z + 2*ζ + u, 2)) end end map +end + +function rotate(m::Int, n::Int) + new_dict = Dict{NTuple{3, Int}, NTuple{3, Int}}() + for (k,j) ∈ enumerate(1:2:m) + for (l,i) ∈ enumerate(n-1:-2:1) + push!(new_dict, (i,j,1) => (i/2 + k - 1, l + k - 1, 1)) + push!(new_dict, (i,j,2) => (i/2 + k - 1, l + k - 1, 2)) + end + end + + for (k,j) ∈ enumerate(2:2:m) + for (l,i) ∈ enumerate(n:-2:1) + push!(new_dict, (i,j,1) => ((i-1)/2 + k, l + k - 1, 1)) + push!(new_dict, (i,j,2) => ((i-1)/2 + k, l + k - 1, 2)) + end + end + new_dict + +end + +function zephyr_lattice_5tuple_rotated(m::Int, n::Int, map::Dict{Int, NTuple{3, Int}}) + rotated_map = rotate(m, n) + new_map = Dict{Int, NTuple{3, Int}}() + for k in keys(map) + push!(new_map, k => rotated_map[map[k]]) + end + new_map end \ No newline at end of file diff --git a/src/utils.jl b/src/utils.jl index b3c8b47..00e9093 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -115,7 +115,7 @@ function zephyr_to_linear(m::Int, t::Int, q::NTuple{5, Int}) M = 2 * m + 1 u, w, k, j, z = q - ind = (((u * M + w) * t + k) * 2 + j) * m + z + ind = (((u * M + w) * t + k) * 2 + j) * m + z + 1 ind end \ No newline at end of file From 3711b8118e59d730738a4d97a14c6c8d90770074 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 14 Jul 2022 22:15:27 +0200 Subject: [PATCH 106/218] clean up --- src/lattice.jl | 54 -------------------------------------------------- 1 file changed, 54 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 372f33c..29d7511 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -3,8 +3,6 @@ export pegasus_lattice, pegasus_lattice_masoud, pegasus_lattice_tomek, - zephyr_lattice, - zephyr_lattice_z1, j_function, zephyr_lattice_5tuple, zephyr_lattice_5tuple_rotated @@ -77,58 +75,6 @@ function zephyr_lattice_z1(size::NTuple{3, Int}) map end - -function zephyr_lattice_boundary(size::NTuple{3, Int}) - m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) - map = Dict{Int, NTuple{3, Int}}() - - for i=1:2*n, j in [j_function(i, n)[begin], j_function(i, n)[end]] - for p in p_func(i, j, t, n, m) - push!(map, (i-1)*(2*n*t) + p*n + (j-m)*2m*t + max(0, i-j) + Int(flag_down(i, j, n, m))*(n-1) + 1 => (i,j,1)) - end - - for q in q_func(i, j, t, n, m) - push!(map, 2*n*t*(2*n+1) + q*m + 1 => (i,j,2)) - end - - end - map - end - - -function flag_left(i::Int, j::Int, n::Int, m::Int) - (i ∈ 1:n && j == m - i + 1) ? true : false -end - -function flag_right(i::Int, j::Int, n::Int, m::Int) - (i ∈ n+1:2*n && j == 3*m + 1 - i) ? true : false -end - -function flag_up(i::Int, j::Int, n::Int, m::Int) - (i == j-n && j ∈ m + 1:2*m ) ? true : false -end - -function flag_down(i::Int, j::Int, n::Int, m::Int) - (i == j + n && j ∈ 1:m ) ? true : false -end - -function flag_horizontal(i::Int, j::Int, n::Int, m::Int) - flag_down(i, j, n, m) || flag_up(i, j, n, m) ? true : false -end - -function flag_vertical(i::Int, j::Int, n::Int, m::Int) - flag_left(i, j, n, m) || flag_right(i, j, n, m) ? true : false -end - - -function p_func(i::Int, j::Int, t::Int, n::Int, m::Int) - flag_horizontal(i, j, n, m) ? collect(0:2:2*t-1) : collect(0:2*t-1) -end - -function q_func(i::Int, j::Int, t::Int, n::Int, m::Int) - flag_vertical(i, j, n, m) ? collect(0:2:2*t-1) : collect(0:2*t-1) -end - function j_function(i::Int, n::Int) if i in collect(1:n) return collect((n + 1 - i):(n + i)) From 96fecc596e65240d1be40b88ebc61302630ee80f Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Tue, 11 Oct 2022 15:21:10 +0200 Subject: [PATCH 107/218] add empty clusters in zephyr --- src/lattice.jl | 44 +++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 43 insertions(+), 1 deletion(-) diff --git a/src/lattice.jl b/src/lattice.jl index 29d7511..68990b6 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -129,11 +129,53 @@ function rotate(m::Int, n::Int) end +function empty_clusters(m::Int, n::Int) + p = (m - 1) / 2 + count = 0 + ii = [] + for (i, j) ∈ enumerate(1:p-1) + count += i + push!(ii, i) + end + (count, reverse(ii)) +end + function zephyr_lattice_5tuple_rotated(m::Int, n::Int, map::Dict{Int, NTuple{3, Int}}) - rotated_map = rotate(m, n) + rotated_map = rotate(m, n) #5, 5, for Z2 new_map = Dict{Int, NTuple{3, Int}}() + + (empty, ii) = empty_clusters(m, n) for k in keys(map) push!(new_map, k => rotated_map[map[k]]) end + + empty_vertices = empty_indexing(m,n) + for (k,l) ∈ enumerate(empty_vertices) + push!(new_map, -k => l) + end new_map +end + +function empty_indexing(m::Int, n::Int) + (empty, ii) = empty_clusters(m, n) + p = Int((m-1)/2) + empty_vertices = [] + for (k,l) ∈ enumerate(ii) + for i in 1:l + push!(empty_vertices, (k, i, 1)) + push!(empty_vertices, (k, i, 2)) + push!(empty_vertices, (k, i + m - p + k - 1, 1)) + push!(empty_vertices, (k, i + m - p + k - 1, 2)) + + end + end + for (k,l) ∈ enumerate(reverse(ii)) + for i in 1:l + push!(empty_vertices, (k + m - p, i, 1)) + push!(empty_vertices, (k + m - p, i, 2)) + push!(empty_vertices, (k + m - p, ii[k] + m - p + k - i, 1)) + push!(empty_vertices, (k + m - p, ii[k] + m - p + k - i, 2)) + end + end + empty_vertices end \ No newline at end of file From ea5a6836ef7c8d8063bca5ef9a87336bb9ee8883 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 12 Jan 2023 11:43:00 +0100 Subject: [PATCH 108/218] add zephyr lattice --- src/lattice.jl | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/src/lattice.jl b/src/lattice.jl index 68990b6..54270bf 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -4,6 +4,7 @@ export pegasus_lattice_masoud, pegasus_lattice_tomek, j_function, + zephyr_lattice, zephyr_lattice_5tuple, zephyr_lattice_5tuple_rotated @@ -83,6 +84,13 @@ function j_function(i::Int, n::Int) end end +zephyr_lattice(size::NTuple{2, Int}) = zephyr_lattice((size[1], size[2], 4)) + +function zephyr_lattice(size::NTuple{3, Int}) + m, n, t = size + zephyr_lattice_5tuple_rotated(m+1, n+1, zephyr_lattice_5tuple((Int(m/2), Int(n/2), t))) +end + function zephyr_lattice_5tuple(size::NTuple{3, Int}) m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) map = Dict{Int, NTuple{3, Int}}() From 421620e437b41e386c5205acaaf7d962c4866599 Mon Sep 17 00:00:00 2001 From: marekrams Date: Wed, 25 Jan 2023 13:20:32 +0100 Subject: [PATCH 109/218] idea projectors --- src/idea_projectors.jl | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) create mode 100644 src/idea_projectors.jl diff --git a/src/idea_projectors.jl b/src/idea_projectors.jl new file mode 100644 index 0000000..630d620 --- /dev/null +++ b/src/idea_projectors.jl @@ -0,0 +1,23 @@ + + +length(lp::list_of_projectors, index::Int64) + return length(lp.data[index]) + +Proj = Union{Vector{Int64}, Cuarray{Int64, 1}} + +struct list_of_projectors + data :: Dict{Int64, Vector{Int64}} # tu kazdy klucz ma element + dataGPU :: Dict{Int64, CuArray{Int64, 1}} + ## jak kontrolowac czy okiekt na gpu czy na cpu? + + +get_projector(lp :: list_of_projectors, index::Int64, onGPU::bool) +return lp.data[index] # dodac element do dataGPU jak jest na cpu, ale nie na gpu ??? + +add_projector(lp :: list_of_projectors, p::Proj) +if p in values(lp.data) + key = key of p_in_lp.data +else + key = generate_new_key + add!(lp.data, key => p) +return key From df61baccafe6869c0e32dc15cc99fb04755a54c0 Mon Sep 17 00:00:00 2001 From: marekrams Date: Wed, 25 Jan 2023 13:47:48 +0100 Subject: [PATCH 110/218] aa --- src/idea_projectors.jl | 29 +++++++++++++++++++++-------- 1 file changed, 21 insertions(+), 8 deletions(-) diff --git a/src/idea_projectors.jl b/src/idea_projectors.jl index 630d620..00073bc 100644 --- a/src/idea_projectors.jl +++ b/src/idea_projectors.jl @@ -1,23 +1,36 @@ -length(lp::list_of_projectors, index::Int64) - return length(lp.data[index]) - Proj = Union{Vector{Int64}, Cuarray{Int64, 1}} + struct list_of_projectors - data :: Dict{Int64, Vector{Int64}} # tu kazdy klucz ma element - dataGPU :: Dict{Int64, CuArray{Int64, 1}} + default_decive = CPU + data :: Dict{devices, Dict{Int64, Proj}} # kazdy klucz ma element na cpu ## jak kontrolowac czy okiekt na gpu czy na cpu? + # osobne miejsce + +length(lp::list_of_projectors, index::Int64) = length(lp.data[lp.default_device][index]) + + +function clear_memory(lp, device) + +function get_projector(lp :: list_of_projectors, index::Proj_keys, device::Int64; view::Symbol = :1D) + # sprawdz czy index in lp.data[device]; jesli nie to go dodaj biorac dane z lp.data[default_device] + return lp.data[device][index] # dodac element do dataGPU jak jest na cpu, ale nie na gpu ??? +end + +function get_projector_CSC(lp :: list_of_projectors, index::Proj_keys, device::Int64) + # sprawdz czy index in lp.data[device]; jesli nie to go dodaj biorac dane z lp.data[default_device] + return lp.data[device][index] # dodac element do dataGPU jak jest na cpu, ale nie na gpu ??? +end -get_projector(lp :: list_of_projectors, index::Int64, onGPU::bool) -return lp.data[index] # dodac element do dataGPU jak jest na cpu, ale nie na gpu ??? -add_projector(lp :: list_of_projectors, p::Proj) +function add_projector(lp :: list_of_projectors, p::Proj) if p in values(lp.data) key = key of p_in_lp.data else key = generate_new_key add!(lp.data, key => p) return key +end \ No newline at end of file From 6446f5193c777adbb58171b4e939755da61b2427 Mon Sep 17 00:00:00 2001 From: Bartek Gardas Date: Wed, 25 Jan 2023 20:21:16 +0100 Subject: [PATCH 111/218] correct syntax --- src/idea_projectors.jl | 39 +++++++++++++-------------------------- 1 file changed, 13 insertions(+), 26 deletions(-) diff --git a/src/idea_projectors.jl b/src/idea_projectors.jl index 00073bc..60a869e 100644 --- a/src/idea_projectors.jl +++ b/src/idea_projectors.jl @@ -1,36 +1,23 @@ -Proj = Union{Vector{Int64}, Cuarray{Int64, 1}} +export + PoolOfProjectors +const Proj{T} = Union{Vector{T}, CuArray{T, 1}} -struct list_of_projectors - default_decive = CPU - data :: Dict{devices, Dict{Int64, Proj}} # kazdy klucz ma element na cpu - ## jak kontrolowac czy okiekt na gpu czy na cpu? - # osobne miejsce +struct PoolOfProjectors{T} + data::Dict{Symbol, Dict{Int, Proj{T}}} + default_device::Symbol -length(lp::list_of_projectors, index::Int64) = length(lp.data[lp.default_device][index]) - - -function clear_memory(lp, device) - -function get_projector(lp :: list_of_projectors, index::Proj_keys, device::Int64; view::Symbol = :1D) - # sprawdz czy index in lp.data[device]; jesli nie to go dodaj biorac dane z lp.data[default_device] - return lp.data[device][index] # dodac element do dataGPU jak jest na cpu, ale nie na gpu ??? + PoolOfProjectors(data:::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(data, :CPU) end +Base.eltype(lp::PoolOfProjectors{T}) where T = T +Base.length(lp::PoolOfProjectors, index::Int) = length(lp.data[lp.default_device][index]) +Base.empty(lp::PoolOfProjectors, device::Symbol) = empty!(lp.data[device]) + +function get_projector!(lp::PoolOfProjectors, index::Int, device::Symbol) -function get_projector_CSC(lp :: list_of_projectors, index::Proj_keys, device::Int64) # sprawdz czy index in lp.data[device]; jesli nie to go dodaj biorac dane z lp.data[default_device] - return lp.data[device][index] # dodac element do dataGPU jak jest na cpu, ale nie na gpu ??? + lp.data[device][index] # dodac element do dataGPU jak jest na cpu, ale nie na gpu ??? end - - -function add_projector(lp :: list_of_projectors, p::Proj) -if p in values(lp.data) - key = key of p_in_lp.data -else - key = generate_new_key - add!(lp.data, key => p) -return key -end \ No newline at end of file From 2893fa4e92e892795f27eec2c07420ce4ce124a4 Mon Sep 17 00:00:00 2001 From: Bartek Gardas Date: Wed, 25 Jan 2023 20:46:48 +0100 Subject: [PATCH 112/218] add comments --- src/idea_projectors.jl | 27 +++++++++++++++++++++++++-- 1 file changed, 25 insertions(+), 2 deletions(-) diff --git a/src/idea_projectors.jl b/src/idea_projectors.jl index 60a869e..a080c4f 100644 --- a/src/idea_projectors.jl +++ b/src/idea_projectors.jl @@ -16,8 +16,31 @@ Base.eltype(lp::PoolOfProjectors{T}) where T = T Base.length(lp::PoolOfProjectors, index::Int) = length(lp.data[lp.default_device][index]) Base.empty(lp::PoolOfProjectors, device::Symbol) = empty!(lp.data[device]) +# TODO This is version for only one GPU function get_projector!(lp::PoolOfProjectors, index::Int, device::Symbol) + if device ∉ lp.data + push!(lp.data[device], index => CuArray(lp.data[default_device][index])) + end + lp.data[device][index] +end - # sprawdz czy index in lp.data[device]; jesli nie to go dodaj biorac dane z lp.data[default_device] - lp.data[device][index] # dodac element do dataGPU jak jest na cpu, ale nie na gpu ??? +#= +buf_a = Mem.alloc(Mem.Unified, sizeof(a)) +d_a = unsafe_wrap(CuArray{Float32,3}, convert(CuPtr{Float32}, buf_a), dims) +finalizer(d_a) do _ + Mem.free(buf_a) +end +copyto!(d_a, a) +=# + +#= +function add_projector!(lp::PoolOfProjectors, p::Proj) + if p in values(lp.data) + key = key of p_in_lp.data + else + key = generate_new_key + push!(lp.data, key => p) + end + key end +=# From cb25079173ffba61474f9e036558b6864f77e21a Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 2 Feb 2023 22:46:02 +0100 Subject: [PATCH 113/218] add periodic lattice (PBCs) --- src/lattice.jl | 26 +++++++++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/src/lattice.jl b/src/lattice.jl index 54270bf..b923784 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -6,7 +6,8 @@ export j_function, zephyr_lattice, zephyr_lattice_5tuple, - zephyr_lattice_5tuple_rotated + zephyr_lattice_5tuple_rotated, + periodic_lattice "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) @@ -186,4 +187,27 @@ function empty_indexing(m::Int, n::Int) end end empty_vertices +end + +function periodic_lattice(size::NTuple{3, Int}) + m, n, t = size + map = super_square_lattice((m, n, t)) + new_map = Dict{Int, NTuple{2, Int}}() + for (key, val) in map + i, j = val + if i <= m/2 + if j <= m/2 + push!(new_map, key => (i, j)) + elseif j > m/2 + push!(new_map, key => (i, m-j+1)) + end + elseif i > m/2 + if j <= m/2 + push!(new_map, key => (m-i+1, j)) + elseif j > m/2 + push!(new_map, key => (m-i+1, m-j+1)) + end + end + end + new_map end \ No newline at end of file From 768fbc84a1d0bacc6f72d5cc71ceaf4ae84ffbd8 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 3 Feb 2023 11:45:53 +0100 Subject: [PATCH 114/218] pool of projectors --- Project.toml | 1 + src/SpinGlassNetworks.jl | 2 ++ src/idea_projectors.jl | 67 ++++++++++++++++++++++++++-------------- test/projectors.jl | 48 ++++++++++++++++++++++++++++ test/runtests.jl | 8 +++-- 5 files changed, 100 insertions(+), 26 deletions(-) create mode 100644 test/projectors.jl diff --git a/Project.toml b/Project.toml index 3cc4808..fabd896 100644 --- a/Project.toml +++ b/Project.toml @@ -11,6 +11,7 @@ LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2" MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5" +CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" [compat] CSV = "0.8" diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 0a0f097..928a068 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -6,6 +6,7 @@ module SpinGlassNetworks using DocStringExtensions using LinearAlgebra, MKL using Base.Cartesian + using CUDA import Base.Prehashed @@ -84,6 +85,7 @@ module SpinGlassNetworks end end + include("idea_projectors.jl") include("ising.jl") include("spectrum.jl") include("lattice.jl") diff --git a/src/idea_projectors.jl b/src/idea_projectors.jl index a080c4f..4545b1e 100644 --- a/src/idea_projectors.jl +++ b/src/idea_projectors.jl @@ -1,46 +1,67 @@ export - PoolOfProjectors + PoolOfProjectors, + get_projector!, + add_projector! const Proj{T} = Union{Vector{T}, CuArray{T, 1}} -struct PoolOfProjectors{T} +struct PoolOfProjectors{T <: Integer} data::Dict{Symbol, Dict{Int, Proj{T}}} default_device::Symbol - PoolOfProjectors(data:::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(data, :CPU) + PoolOfProjectors(data::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(Dict(:CPU => data), :CPU) + PoolOfProjectors{T}() where T = new{T}(Dict(:CPU => Dict{Int, Proj{T}}()), :CPU) end + Base.eltype(lp::PoolOfProjectors{T}) where T = T +Base.length(lp::PoolOfProjectors) = length(lp.data[lp.default_device]) Base.length(lp::PoolOfProjectors, index::Int) = length(lp.data[lp.default_device][index]) -Base.empty(lp::PoolOfProjectors, device::Symbol) = empty!(lp.data[device]) +Base.length(lp::PoolOfProjectors, device::Symbol) = length(lp.data[device]) +Base.empty!(lp::PoolOfProjectors, device::Symbol) = empty!(lp.data[device]) + +get_projector!(lp::PoolOfProjectors, index::Int) = get_projector!(lp, index, lp.default_device) # TODO This is version for only one GPU -function get_projector!(lp::PoolOfProjectors, index::Int, device::Symbol) - if device ∉ lp.data - push!(lp.data[device], index => CuArray(lp.data[default_device][index])) +function get_projector!(lp::PoolOfProjectors{T}, index::Int, device::Symbol) where T <: Integer + if device ∉ keys(lp.data) + push!(lp.data, device => Dict{Int, Proj{T}}()) end - lp.data[device][index] -end -#= -buf_a = Mem.alloc(Mem.Unified, sizeof(a)) -d_a = unsafe_wrap(CuArray{Float32,3}, convert(CuPtr{Float32}, buf_a), dims) -finalizer(d_a) do _ - Mem.free(buf_a) + if index ∉ keys(lp.data[device]) + if device == :GPU + p = CuArray{T}(lp.data[lp.default_device][index]) + elseif device == :CPU + p = Array{T}(lp.data[lp.default_device][index]) + else + throw(ArgumentError("device should be :CPU or :GPU")) + end + push!(lp.data[device], index => p) + end + lp.data[device][index] end -copyto!(d_a, a) -=# -#= -function add_projector!(lp::PoolOfProjectors, p::Proj) - if p in values(lp.data) - key = key of p_in_lp.data +function add_projector!(lp::PoolOfProjectors{T}, p::Proj) where T <: Integer + if lp.default_device == :CPU + p = Array{T}(p) + elseif lp.default_device == :GPU + p = CuArray{T}(p) + else + throw(ArgumentError("default_device should be :CPU or :GPU")) + end + if p in values(lp.data[lp.default_device]) + key = -1 + for guess in keys(lp.data[lp.default_device]) + if lp.data[lp.default_device][guess] == p + key = guess + break + end + end else - key = generate_new_key - push!(lp.data, key => p) + key = length(lp.data[lp.default_device]) + 1 + push!(lp.data[lp.default_device], key => p) end key end -=# diff --git a/test/projectors.jl b/test/projectors.jl new file mode 100644 index 0000000..e24d7fb --- /dev/null +++ b/test/projectors.jl @@ -0,0 +1,48 @@ + +@testset "Add and get from pool of projectors" begin + @testset "Start with empty pool and add elements to it" begin + lp = PoolOfProjectors{Int64}() + @test length(lp) == 0 + + p1 = [1, 1, 2, 2, 3, 3] + p2 = [1, 2, 1, 3] + k = add_projector!(lp, p1) + @test k == 1 + @test length(lp) == 1 + + k = add_projector!(lp, p1) + @test k == 1 + @test length(lp) == 1 + + k = add_projector!(lp, p2) + @test k == 2 + @test length(lp) == 2 + + @test get_projector!(lp, 1) == p1 + @test get_projector!(lp, 2) == p2 + + empty!(lp, lp.default_device) + @test length(lp) == 0 + end + + @testset "Different devices" begin + for T ∈ [Int16, Int32, Int64] + lp = PoolOfProjectors{T}() + p1 = Vector{T}([1, 1, 2, 2, 3, 3]) + p2 = Vector{T}([1, 2, 1, 3]) + k = add_projector!(lp, p1) + k = add_projector!(lp, p2) + + @test typeof(get_projector!(lp, 2, :CPU)) <: Array{T, 1} + @test typeof(get_projector!(lp, 1, :GPU)) <: CuArray{T, 1} + @test length(lp, :GPU) == 1 + @test length(lp, :CPU) == 2 + + @test typeof(get_projector!(lp, 1, :GPU)) <: CuArray{T, 1} + @test length(lp, :GPU) == 1 + + @test typeof(get_projector!(lp, 2, :GPU)) <: CuArray{T, 1} + @test length(lp, :GPU) == 2 + end + end +end diff --git a/test/runtests.jl b/test/runtests.jl index a31f9f2..9f8a22b 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -4,6 +4,7 @@ using LightGraphs using MetaGraphs using Logging using Test +using CUDA Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) @@ -27,9 +28,10 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) end my_tests = [ - "ising.jl", - "factor.jl", - "utils.jl", + #"ising.jl", + #"factor.jl", + # "utils.jl", + "projectors.jl" ] for my_test ∈ my_tests From aad83de100701dd6f289e127c5c0c220218dd451 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 3 Feb 2023 12:10:59 +0100 Subject: [PATCH 115/218] fg --- src/factor.jl | 12 ++++++++++-- test/factor.jl | 28 +++++++++++++++++----------- test/runtests.jl | 8 ++++---- 3 files changed, 31 insertions(+), 17 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 5459199..08a28e3 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -44,6 +44,8 @@ function factor_graph( set_props!(fg, v, Dict(:cluster => cl, :spectrum => sp)) end + lp = PoolOfProjectors{Int64}() # TODO: Have consistent way to specify type of Integers + for (i, v) ∈ enumerate(vertices(fg)), w ∈ vertices(fg)[i+1:end] cl1, cl2 = get_prop(fg, v, :cluster), get_prop(fg, w, :cluster) outer_edges, J = inter_cluster_edges(ig, cl1, cl2) @@ -63,12 +65,18 @@ function factor_graph( en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) add_edge!(fg, v, w) + + kl = add_projector!(lp, pl) + kr = add_projector!(lp, pr) + set_props!( - fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) + fg, v, w, Dict(:outer_edges => outer_edges, :pl => kl, :en => en, :pr => kr) ) end end - fg + # TODO: now we return two structure; Graph (contains keys of projectors); and our dict of projectors + # TODO: this should be cleaned + (fg, lp) end function factor_graph( diff --git a/test/factor.jl b/test/factor.jl index 8750699..0414cba 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -14,7 +14,7 @@ enum(vec) = Dict(v => i for (i, v) ∈ enumerate(vec)) ig = ising_graph(instance) - fg = factor_graph(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t)) ) + fg, lp = factor_graph(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t))) @test collect(vertices(fg)) == [(i, j) for i ∈ 1:m for j ∈ 1:n] @@ -80,19 +80,21 @@ end bond_dimensions = [2, 2, 8, 4, 2, 2, 8] - fg = factor_graph( + fg, lp = factor_graph( ising_graph(instance), spectrum=full_spectrum, cluster_assignment_rule=super_square_lattice((m, n, t)), ) for (bd, e) in zip(bond_dimensions, edges(fg)) - pl, en, pr = get_prop(fg, e, :pl), get_prop(fg, e, :en), get_prop(fg, e, :pr) + kl, en, kr = get_prop(fg, e, :pl), get_prop(fg, e, :en), get_prop(fg, e, :pr) @test minimum(size(en)) == bd + @test maximum(get_projector!(lp, kl)) == size(en, 1) + @test maximum(get_projector!(lp, kr)) == size(en, 2) end for ((i, j), cedge) ∈ cedges - pl, en, pr = get_prop(fg, i, j, :pl), get_prop(fg, i, j, :en), get_prop(fg, i, j, :pr) + kl, en, kr = get_prop(fg, i, j, :pl), get_prop(fg, i, j, :en), get_prop(fg, i, j, :pr) base_i = all_states(rank[i]) base_j = all_states(rank[j]) @@ -114,6 +116,8 @@ end energy[ii, jj] = eij end end + pl = get_projector!(lp, kl) + pr = get_projector!(lp, kr) @test energy ≈ en[pl, pr] end @@ -155,7 +159,7 @@ fg_state_to_spin = [ ] @testset "Decoding solution gives correct spin assignment" begin - fg = create_example_factor_graph() + fg, lp = create_example_factor_graph() for (state, spin_values) ∈ fg_state_to_spin d = decode_factor_graph_state(fg, state) states = collect(values(d))[collect(keys(d))] @@ -213,17 +217,17 @@ function create_larger_example_factor_graph() 9 => (2, 2) ) - fg = factor_graph( + fg, lp = factor_graph( ig, Dict{NTuple{2, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule, ) - ig, fg + ig, fg, lp end -function factor_graph_energy(fg, state) +function factor_graph_energy(fg, lp, state) # This is highly inefficient, but simple, which makes it suitable for testing. # If such a function is needed elsewhere, we need to implement it properly. total_en = 0.0 @@ -236,7 +240,9 @@ function factor_graph_energy(fg, state) # Collect inter-cluster terms for edge ∈ edges(fg) i, j = fg.reverse_label_map[src(edge)], fg.reverse_label_map[dst(edge)] - pl, en, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :en), get_prop(fg, edge, :pr) + kl, en, kr = get_prop(fg, edge, :pl), get_prop(fg, edge, :en), get_prop(fg, edge, :pr) + pl = get_projector!(lp, kl) + pr = get_projector!(lp, kr) edge_energy = en[pl, pr] total_en += edge_energy[state[i], state[j]] end @@ -246,7 +252,7 @@ end @testset "Decoding solution gives spins configuration with corresponding energies" begin - ig, fg = create_larger_example_factor_graph() + ig, fg, lp = create_larger_example_factor_graph() # Corresponding bases sizes for each cluster are 16, 4, 4, 2. all_states = [[i, j, k, l] for i ∈ 1:16 for j ∈ 1:4 for k ∈ 1:4 for l ∈ 1:2] @@ -257,6 +263,6 @@ end for (k, v) ∈ d spins[k] = v end - @test factor_graph_energy(fg, state) ≈ energy([Int.(spins)], ig)[] + @test factor_graph_energy(fg, lp, state) ≈ energy([Int.(spins)], ig)[] end end diff --git a/test/runtests.jl b/test/runtests.jl index 9f8a22b..be20f57 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -28,10 +28,10 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) end my_tests = [ - #"ising.jl", - #"factor.jl", - # "utils.jl", - "projectors.jl" + "ising.jl", + "factor.jl", + "projectors.jl", + "utils.jl", ] for my_test ∈ my_tests From 624aa019ebfd43dda12c9d48b552f8186f146002 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 3 Feb 2023 14:02:13 +0100 Subject: [PATCH 116/218] energy --- src/factor.jl | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 08a28e3..671232d 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -131,11 +131,13 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en end -function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} +function energy(fg::LabelledGraph{S, T}, lp::PoolOfProjectors, σ::Dict{T, Int}) where {S, T} en_fg = 0.0 for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end for edge ∈ edges(fg) - pl, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) + kl, kr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) + pl = get_projector!(lp, kl) + pr = get_projector!(lp, kr) en = get_prop(fg, edge, :en) en_fg += en[pl[σ[src(edge)]], pr[σ[dst(edge)]]] end From 25c580f96baf6948403ce37fe3abea192408570b Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 3 Feb 2023 16:32:30 +0100 Subject: [PATCH 117/218] decode states in sampling --- src/lattice.jl | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index b923784..9833229 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -190,8 +190,9 @@ function empty_indexing(m::Int, n::Int) end function periodic_lattice(size::NTuple{3, Int}) - m, n, t = size - map = super_square_lattice((m, n, t)) + mm, nn, tt = size + m, n = 2*mm, 2*nn + map = super_square_lattice((m, n, 1)) new_map = Dict{Int, NTuple{2, Int}}() for (key, val) in map i, j = val From 1fd6d7ce9bcf47bb91a681d3a8e5e4bcbdc1e0eb Mon Sep 17 00:00:00 2001 From: marekrams Date: Sat, 4 Feb 2023 08:52:15 +0100 Subject: [PATCH 118/218] lp size --- src/idea_projectors.jl | 11 +++++++++-- test/projectors.jl | 5 +++++ 2 files changed, 14 insertions(+), 2 deletions(-) diff --git a/src/idea_projectors.jl b/src/idea_projectors.jl index 4545b1e..3b7ec55 100644 --- a/src/idea_projectors.jl +++ b/src/idea_projectors.jl @@ -10,9 +10,14 @@ const Proj{T} = Union{Vector{T}, CuArray{T, 1}} struct PoolOfProjectors{T <: Integer} data::Dict{Symbol, Dict{Int, Proj{T}}} default_device::Symbol + sizes::Dict{Int, Int} - PoolOfProjectors(data::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(Dict(:CPU => data), :CPU) - PoolOfProjectors{T}() where T = new{T}(Dict(:CPU => Dict{Int, Proj{T}}()), :CPU) + PoolOfProjectors(data::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(Dict(:CPU => data), + :CPU, + Dict{Int, Int}(k => maximum(v) for (k, v) ∈ data)) + PoolOfProjectors{T}() where T = new{T}(Dict(:CPU => Dict{Int, Proj{T}}()), + :CPU, + Dict{Int, Int}()) end @@ -21,6 +26,7 @@ Base.length(lp::PoolOfProjectors) = length(lp.data[lp.default_device]) Base.length(lp::PoolOfProjectors, index::Int) = length(lp.data[lp.default_device][index]) Base.length(lp::PoolOfProjectors, device::Symbol) = length(lp.data[device]) Base.empty!(lp::PoolOfProjectors, device::Symbol) = empty!(lp.data[device]) +Base.size(lp::PoolOfProjectors, index::Int) = lp.sizes[index] get_projector!(lp::PoolOfProjectors, index::Int) = get_projector!(lp, index, lp.default_device) @@ -62,6 +68,7 @@ function add_projector!(lp::PoolOfProjectors{T}, p::Proj) where T <: Integer else key = length(lp.data[lp.default_device]) + 1 push!(lp.data[lp.default_device], key => p) + push!(lp.sizes, key => maximum(p)) end key end diff --git a/test/projectors.jl b/test/projectors.jl index e24d7fb..bc42434 100644 --- a/test/projectors.jl +++ b/test/projectors.jl @@ -21,6 +21,11 @@ @test get_projector!(lp, 1) == p1 @test get_projector!(lp, 2) == p2 + @test length(lp, 1) == 6 + @test length(lp, 2) == 4 + @test size(lp, 1) == 3 + @test size(lp, 2) == 3 + empty!(lp, lp.default_device) @test length(lp) == 0 end From 0bbbf19d35e8afb66d83f878d27df1201f010701 Mon Sep 17 00:00:00 2001 From: marekrams Date: Wed, 8 Feb 2023 11:02:35 +0100 Subject: [PATCH 119/218] remove PoolOfProjectors --- src/SpinGlassNetworks.jl | 2 -- src/factor.jl | 16 +++------ src/idea_projectors.jl | 74 ---------------------------------------- test/factor.jl | 30 +++++++--------- test/projectors.jl | 53 ---------------------------- test/runtests.jl | 1 - 6 files changed, 17 insertions(+), 159 deletions(-) delete mode 100644 src/idea_projectors.jl delete mode 100644 test/projectors.jl diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 928a068..0a0f097 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -6,7 +6,6 @@ module SpinGlassNetworks using DocStringExtensions using LinearAlgebra, MKL using Base.Cartesian - using CUDA import Base.Prehashed @@ -85,7 +84,6 @@ module SpinGlassNetworks end end - include("idea_projectors.jl") include("ising.jl") include("spectrum.jl") include("lattice.jl") diff --git a/src/factor.jl b/src/factor.jl index 671232d..e1f25f6 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -44,8 +44,6 @@ function factor_graph( set_props!(fg, v, Dict(:cluster => cl, :spectrum => sp)) end - lp = PoolOfProjectors{Int64}() # TODO: Have consistent way to specify type of Integers - for (i, v) ∈ enumerate(vertices(fg)), w ∈ vertices(fg)[i+1:end] cl1, cl2 = get_prop(fg, v, :cluster), get_prop(fg, w, :cluster) outer_edges, J = inter_cluster_edges(ig, cl1, cl2) @@ -65,18 +63,14 @@ function factor_graph( en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) add_edge!(fg, v, w) - - kl = add_projector!(lp, pl) - kr = add_projector!(lp, pr) - set_props!( - fg, v, w, Dict(:outer_edges => outer_edges, :pl => kl, :en => en, :pr => kr) + fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) ) end end # TODO: now we return two structure; Graph (contains keys of projectors); and our dict of projectors # TODO: this should be cleaned - (fg, lp) + fg end function factor_graph( @@ -131,13 +125,11 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en end -function energy(fg::LabelledGraph{S, T}, lp::PoolOfProjectors, σ::Dict{T, Int}) where {S, T} +function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_fg = 0.0 for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end for edge ∈ edges(fg) - kl, kr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) - pl = get_projector!(lp, kl) - pr = get_projector!(lp, kr) + pl, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) en = get_prop(fg, edge, :en) en_fg += en[pl[σ[src(edge)]], pr[σ[dst(edge)]]] end diff --git a/src/idea_projectors.jl b/src/idea_projectors.jl deleted file mode 100644 index 3b7ec55..0000000 --- a/src/idea_projectors.jl +++ /dev/null @@ -1,74 +0,0 @@ - - -export - PoolOfProjectors, - get_projector!, - add_projector! - -const Proj{T} = Union{Vector{T}, CuArray{T, 1}} - -struct PoolOfProjectors{T <: Integer} - data::Dict{Symbol, Dict{Int, Proj{T}}} - default_device::Symbol - sizes::Dict{Int, Int} - - PoolOfProjectors(data::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(Dict(:CPU => data), - :CPU, - Dict{Int, Int}(k => maximum(v) for (k, v) ∈ data)) - PoolOfProjectors{T}() where T = new{T}(Dict(:CPU => Dict{Int, Proj{T}}()), - :CPU, - Dict{Int, Int}()) -end - - -Base.eltype(lp::PoolOfProjectors{T}) where T = T -Base.length(lp::PoolOfProjectors) = length(lp.data[lp.default_device]) -Base.length(lp::PoolOfProjectors, index::Int) = length(lp.data[lp.default_device][index]) -Base.length(lp::PoolOfProjectors, device::Symbol) = length(lp.data[device]) -Base.empty!(lp::PoolOfProjectors, device::Symbol) = empty!(lp.data[device]) -Base.size(lp::PoolOfProjectors, index::Int) = lp.sizes[index] - -get_projector!(lp::PoolOfProjectors, index::Int) = get_projector!(lp, index, lp.default_device) - -# TODO This is version for only one GPU -function get_projector!(lp::PoolOfProjectors{T}, index::Int, device::Symbol) where T <: Integer - if device ∉ keys(lp.data) - push!(lp.data, device => Dict{Int, Proj{T}}()) - end - - if index ∉ keys(lp.data[device]) - if device == :GPU - p = CuArray{T}(lp.data[lp.default_device][index]) - elseif device == :CPU - p = Array{T}(lp.data[lp.default_device][index]) - else - throw(ArgumentError("device should be :CPU or :GPU")) - end - push!(lp.data[device], index => p) - end - lp.data[device][index] -end - -function add_projector!(lp::PoolOfProjectors{T}, p::Proj) where T <: Integer - if lp.default_device == :CPU - p = Array{T}(p) - elseif lp.default_device == :GPU - p = CuArray{T}(p) - else - throw(ArgumentError("default_device should be :CPU or :GPU")) - end - if p in values(lp.data[lp.default_device]) - key = -1 - for guess in keys(lp.data[lp.default_device]) - if lp.data[lp.default_device][guess] == p - key = guess - break - end - end - else - key = length(lp.data[lp.default_device]) + 1 - push!(lp.data[lp.default_device], key => p) - push!(lp.sizes, key => maximum(p)) - end - key -end diff --git a/test/factor.jl b/test/factor.jl index 0414cba..ef11a14 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -14,7 +14,7 @@ enum(vec) = Dict(v => i for (i, v) ∈ enumerate(vec)) ig = ising_graph(instance) - fg, lp = factor_graph(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t))) + fg = factor_graph(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t))) @test collect(vertices(fg)) == [(i, j) for i ∈ 1:m for j ∈ 1:n] @@ -80,21 +80,21 @@ end bond_dimensions = [2, 2, 8, 4, 2, 2, 8] - fg, lp = factor_graph( + fg = factor_graph( ising_graph(instance), spectrum=full_spectrum, cluster_assignment_rule=super_square_lattice((m, n, t)), ) for (bd, e) in zip(bond_dimensions, edges(fg)) - kl, en, kr = get_prop(fg, e, :pl), get_prop(fg, e, :en), get_prop(fg, e, :pr) + pl, en, pr = get_prop(fg, e, :pl), get_prop(fg, e, :en), get_prop(fg, e, :pr) @test minimum(size(en)) == bd - @test maximum(get_projector!(lp, kl)) == size(en, 1) - @test maximum(get_projector!(lp, kr)) == size(en, 2) + @test maximum(pl) == size(en, 1) + @test maximum(pr) == size(en, 2) end for ((i, j), cedge) ∈ cedges - kl, en, kr = get_prop(fg, i, j, :pl), get_prop(fg, i, j, :en), get_prop(fg, i, j, :pr) + pl, en, pr = get_prop(fg, i, j, :pl), get_prop(fg, i, j, :en), get_prop(fg, i, j, :pr) base_i = all_states(rank[i]) base_j = all_states(rank[j]) @@ -116,8 +116,6 @@ end energy[ii, jj] = eij end end - pl = get_projector!(lp, kl) - pr = get_projector!(lp, kr) @test energy ≈ en[pl, pr] end @@ -159,7 +157,7 @@ fg_state_to_spin = [ ] @testset "Decoding solution gives correct spin assignment" begin - fg, lp = create_example_factor_graph() + fg = create_example_factor_graph() for (state, spin_values) ∈ fg_state_to_spin d = decode_factor_graph_state(fg, state) states = collect(values(d))[collect(keys(d))] @@ -217,17 +215,17 @@ function create_larger_example_factor_graph() 9 => (2, 2) ) - fg, lp = factor_graph( + fg = factor_graph( ig, Dict{NTuple{2, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule, ) - ig, fg, lp + ig, fg end -function factor_graph_energy(fg, lp, state) +function factor_graph_energy(fg, state) # This is highly inefficient, but simple, which makes it suitable for testing. # If such a function is needed elsewhere, we need to implement it properly. total_en = 0.0 @@ -240,9 +238,7 @@ function factor_graph_energy(fg, lp, state) # Collect inter-cluster terms for edge ∈ edges(fg) i, j = fg.reverse_label_map[src(edge)], fg.reverse_label_map[dst(edge)] - kl, en, kr = get_prop(fg, edge, :pl), get_prop(fg, edge, :en), get_prop(fg, edge, :pr) - pl = get_projector!(lp, kl) - pr = get_projector!(lp, kr) + pl, en, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :en), get_prop(fg, edge, :pr) edge_energy = en[pl, pr] total_en += edge_energy[state[i], state[j]] end @@ -252,7 +248,7 @@ end @testset "Decoding solution gives spins configuration with corresponding energies" begin - ig, fg, lp = create_larger_example_factor_graph() + ig, fg = create_larger_example_factor_graph() # Corresponding bases sizes for each cluster are 16, 4, 4, 2. all_states = [[i, j, k, l] for i ∈ 1:16 for j ∈ 1:4 for k ∈ 1:4 for l ∈ 1:2] @@ -263,6 +259,6 @@ end for (k, v) ∈ d spins[k] = v end - @test factor_graph_energy(fg, lp, state) ≈ energy([Int.(spins)], ig)[] + @test factor_graph_energy(fg, state) ≈ energy([Int.(spins)], ig)[] end end diff --git a/test/projectors.jl b/test/projectors.jl deleted file mode 100644 index bc42434..0000000 --- a/test/projectors.jl +++ /dev/null @@ -1,53 +0,0 @@ - -@testset "Add and get from pool of projectors" begin - @testset "Start with empty pool and add elements to it" begin - lp = PoolOfProjectors{Int64}() - @test length(lp) == 0 - - p1 = [1, 1, 2, 2, 3, 3] - p2 = [1, 2, 1, 3] - k = add_projector!(lp, p1) - @test k == 1 - @test length(lp) == 1 - - k = add_projector!(lp, p1) - @test k == 1 - @test length(lp) == 1 - - k = add_projector!(lp, p2) - @test k == 2 - @test length(lp) == 2 - - @test get_projector!(lp, 1) == p1 - @test get_projector!(lp, 2) == p2 - - @test length(lp, 1) == 6 - @test length(lp, 2) == 4 - @test size(lp, 1) == 3 - @test size(lp, 2) == 3 - - empty!(lp, lp.default_device) - @test length(lp) == 0 - end - - @testset "Different devices" begin - for T ∈ [Int16, Int32, Int64] - lp = PoolOfProjectors{T}() - p1 = Vector{T}([1, 1, 2, 2, 3, 3]) - p2 = Vector{T}([1, 2, 1, 3]) - k = add_projector!(lp, p1) - k = add_projector!(lp, p2) - - @test typeof(get_projector!(lp, 2, :CPU)) <: Array{T, 1} - @test typeof(get_projector!(lp, 1, :GPU)) <: CuArray{T, 1} - @test length(lp, :GPU) == 1 - @test length(lp, :CPU) == 2 - - @test typeof(get_projector!(lp, 1, :GPU)) <: CuArray{T, 1} - @test length(lp, :GPU) == 1 - - @test typeof(get_projector!(lp, 2, :GPU)) <: CuArray{T, 1} - @test length(lp, :GPU) == 2 - end - end -end diff --git a/test/runtests.jl b/test/runtests.jl index be20f57..19f8d36 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -30,7 +30,6 @@ end my_tests = [ "ising.jl", "factor.jl", - "projectors.jl", "utils.jl", ] From 041435ce5701b3c99c5dc0f6e8b381db69b004af Mon Sep 17 00:00:00 2001 From: marekrams Date: Wed, 8 Feb 2023 13:09:58 +0100 Subject: [PATCH 120/218] no CUDA --- Project.toml | 1 - test/runtests.jl | 2 +- 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/Project.toml b/Project.toml index fabd896..3cc4808 100644 --- a/Project.toml +++ b/Project.toml @@ -11,7 +11,6 @@ LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2" MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5" -CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" [compat] CSV = "0.8" diff --git a/test/runtests.jl b/test/runtests.jl index 19f8d36..8e88be1 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -4,7 +4,7 @@ using LightGraphs using MetaGraphs using Logging using Test -using CUDA + Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) From d871d72db6a595b8a75a14995f6c71902455aa60 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Mon, 13 Feb 2023 12:25:28 +0100 Subject: [PATCH 121/218] removed unnecessary functions --- src/utils.jl | 109 +-------------------------------------------------- 1 file changed, 2 insertions(+), 107 deletions(-) diff --git a/src/utils.jl b/src/utils.jl index 00e9093..e40d502 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -1,117 +1,12 @@ -using LabelledGraphs - export - linear_to_pegasus, - pegasus_to_nice, - linear_to_nice, - nice_to_dattani, - dattani_to_linear, - droplets_to_pegasus_nice, - linear_to_zephyr, zephyr_to_linear - -const Instance = Union{String, Dict} - -""" -Rewriten from Dwave-networkx lib -""" -function linear_to_pegasus(size::Int, r::Int) - m, m1 = size, size - 1 - r, z = divrem(r, m1) - r, k = divrem(r, 12) - u, w = divrem(r, m) - (u, w, k, z) -end - -""" -Rewriten from Dwave-networkx -""" -function pegasus_to_nice(p::NTuple{4, Int}) #TODO: Write it better. Now it is rewriten verbatim. - u, w, k, z = p - - t = (2 - u - (2 * u - 1) * floor(k / 4)) % 3 - if t < 0 t = t+3 end - - if t == 0 - if u > 0 - y = w-1 - x = z - else - y = z - x = w - end - return (round(Int, t), y, x, u, k-4) - - elseif t == 1 - if u > 0 - y = w-1 - x = z - k1 = k - else - y = z - x = w - k1 = k-8 - end - return (round(Int, t), y, x, u, k1) - - elseif t == 2 - if u > 0 - y = w - x = z - k1 = k-8 - else - y = z - x = w-1 - k1 = k - end - return (round(Int, t), y, x, u, k1) - end -end - -""" -Rewriten from Dwave-networkx -""" -linear_to_nice(size::Int, r::Int) = pegasus_to_nice(linear_to_pegasus(size, r)) - -""" -Based on [1] https://arxiv.org/abs/1901.07636 -Changes pegasus_nice tuple into tuple from [1]. -It is worth noting that two last indexes in [1] -corespond to binary representatation of number from [0, 1, 2, 3] -""" -nice_to_dattani(pn::NTuple{5, Int}) = (pn[3], pn[2], pn[1], pn[4], pn[5]) - -""" -Changes tuple into linear index inspired by Dattani's paper -""" -function dattani_to_linear(size::Int, d::NTuple{5, Int}) - 24 * (size - 1) * d[1] + 24 * d[2] + 8 * d[3] + 4 * d[4] + d[5] + 1 -end - -""" -Rewriten from Dwave-networkx -""" -function linear_to_zephyr(m::Int, t::Int, ind::Int) - # m - Grid parameter for the Zephyr lattice. - # t - Tile parameter for the Zephyr lattice; must be even. - - M = 2 * m + 1 - - ind, z = divrem(ind, m) - ind, j = divrem(ind, 2) - ind, k = divrem(ind, t) - u, w = divrem(ind, M) - - (u, w, k, j, z) -end - """ Rewriten from Dwave-networkx +m - Grid parameter for the Zephyr lattice. +t - Tile parameter for the Zephyr lattice; must be even. """ function zephyr_to_linear(m::Int, t::Int, q::NTuple{5, Int}) - # m - Grid parameter for the Zephyr lattice. - # t - Tile parameter for the Zephyr lattice; must be even. M = 2 * m + 1 u, w, k, j, z = q From 7d43d6489091d9736d4d320a50bb458d02f3bcd2 Mon Sep 17 00:00:00 2001 From: Bartek Date: Sat, 25 Feb 2023 12:05:00 +0000 Subject: [PATCH 122/218] start working on a proper types propagation --- src/factor.jl | 50 ++++++++++------------------ src/ising.jl | 45 ++++++++++++------------- src/lattice.jl | 50 +++++++++++----------------- src/spectrum.jl | 18 +++++----- src/utils.jl | 7 ++-- test/ising.jl | 85 ++++++++++++++++++++++-------------------------- test/runtests.jl | 4 +-- test/utils.jl | 75 +++--------------------------------------- 8 files changed, 115 insertions(+), 219 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index e1f25f6..23cd9e7 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -7,10 +7,12 @@ export energy, cluster_size +const FactorGraph{T} = LabelledGraph{MetaDiGraph{Int64, T}, Int64} + """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ -function split_into_clusters(ig::LabelledGraph{S, T}, assignment_rule) where {S, T} +function split_into_clusters(ig::IsingGraph, assignment_rule) cluster_id_to_verts = Dict(i => T[] for i in values(assignment_rule)) for v in vertices(ig) push!(cluster_id_to_verts[assignment_rule[v]], v) end Dict(i => first(cluster(ig, verts)) for (i, verts) ∈ cluster_id_to_verts) @@ -21,23 +23,17 @@ Create factor graph. Factor graph order introduced as a natural order in factor graph coordinates. """ function factor_graph( - ig::IsingGraph, - num_states_cl::Int; - spectrum::Function=full_spectrum, - cluster_assignment_rule::Dict{Int, T} # e.g. square lattice -) where T + ig::IsingGraph, num_states_cl::Int; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict +) ns = Dict(i => num_states_cl for i ∈ Set(values(cluster_assignment_rule))) factor_graph(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end function factor_graph( - ig::IsingGraph, - num_states_cl::Dict{T, Int}; - spectrum::Function=full_spectrum, - cluster_assignment_rule::Dict{Int, T} + ig::IsingGraph{T}, num_states_cl::Dict{T, Int}; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict ) where T L = maximum(values(cluster_assignment_rule)) - fg = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) + fg = FactorGraph{T}(sort(unique(values(cluster_assignment_rule)))) for (v, cl) ∈ split_into_clusters(ig, cluster_assignment_rule) sp = spectrum(cl, num_states=get(num_states_cl, v, basis_size(cl))) @@ -63,22 +59,14 @@ function factor_graph( en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) add_edge!(fg, v, w) - set_props!( - fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) - ) + set_props!(fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr)) end end - # TODO: now we return two structure; Graph (contains keys of projectors); and our dict of projectors - # TODO: this should be cleaned fg end -function factor_graph( - ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} -) where T - factor_graph( - ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule - ) +function factor_graph(ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict) + factor_graph(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end function rank_reveal(energy, order=:PE) @@ -94,7 +82,7 @@ Returns Dict(vertex of ising graph -> spin value) Assumes that state has the same order as vertices in factor graph! TODO: check the order consistency over external packages. """ -function decode_factor_graph_state(fg, state::Vector{Int}) +function decode_factor_graph_state(fg::FactorGraph, state::Vector{Int}) ret = Dict{Int, Int}() for (i, vert) ∈ zip(state, vertices(fg)) spins = get_prop(fg, vert, :cluster).labels @@ -110,23 +98,23 @@ end """ TODO: write it better (for now this is only for testing). """ -function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) - en = 0.0 +function energy(ig::IsingGraph{T}, ig_state::Dict{Int, Int}) where T + en = zero(T) for (i, σ) ∈ ig_state en += get_prop(ig, i, :h) * σ for (j, η) ∈ ig_state if has_edge(ig, i, j) - en += σ * get_prop(ig, i, j, :J) * η / 2.0 + en += σ * get_prop(ig, i, j, :J) * η / T(2) elseif has_edge(ig, j, i) - en += σ * get_prop(ig, j, i, :J) * η / 2.0 + en += σ * get_prop(ig, j, i, :J) * η / T(2) end end end en end -function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} - en_fg = 0.0 +function energy(fg::FactorGraph{T}, σ::Dict{S, Int}) where {S, T} + en_fg = zero(T) for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end for edge ∈ edges(fg) pl, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) @@ -136,6 +124,4 @@ function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_fg end -function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} - length(get_prop(factor_graph, vertex, :spectrum).energies) -end +cluster_size(fg::FactorGraph, vertex) = length(get_prop(fg, vertex, :spectrum).energies) diff --git a/src/ising.jl b/src/ising.jl index c5af076..b08659e 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -13,7 +13,7 @@ export prune const Instance = Union{String, Dict} -const IsingGraph = LabelledGraph{MetaGraph{Int64, Float64}, Int64} +const IsingGraph{T} = LabelledGraph{MetaGraph{Int64, T}} function unique_nodes(ising_tuples) sort(collect(Set(Iterators.flatten((i, j) for (i, j, _) ∈ ising_tuples)))) @@ -22,18 +22,16 @@ end """ Creates Ising graph, H = sgn * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) """ -function ising_graph( - instance::Instance; sgn::Real=1.0, rank_override::Dict{Int, Int}=Dict{Int, Int}() -) +function ising_graph(::Type{T}, inst::Instance; sgn::Real=1, rank_override::Dict=Dict{Int, Int}()) where T # load the Ising instance - if instance isa String - ising = CSV.File(instance, types = [Int, Int, Float64], header=0, comment = "#") + if inst isa String + ising = CSV.File(inst, types = [Int, Int, T], header=0, comment = "#") else - ising = [(i, j, J) for ((i, j), J) ∈ instance] + ising = [(i, j, T(J)) for ((i, j), J) ∈ inst] end - ig = LabelledGraph{MetaGraph}(unique_nodes(ising)) + ig = IsingGraph{T}(unique_nodes(ising)) - set_prop!.(Ref(ig), vertices(ig), :h, 0) + set_prop!.(Ref(ig), vertices(ig), :h, zero(T)) foreach(v -> set_prop!(ig, v, :rank, get(rank_override, v, 2)), vertices(ig)) for (i, j, v) ∈ ising @@ -45,19 +43,24 @@ function ising_graph( set_prop!(ig, i, j, :J, v) end end - set_prop!( - ig, :rank, Dict{Int, Int}(v => get(rank_override, v, 2) for v in vertices(ig)) - ) + set_prop!(ig, :rank, Dict(v => get(rank_override, v, 2) for v in vertices(ig))) ig end + +function ising_graph(inst::Instance; sgn::Real=1, rank_override::Dict=Dict{Int, Int}()) + ising_graph(Float64, inst; sgn = sgn, rank_override = rank_override) +end +Base.eltype(ig::IsingGraph{T}) where T = T + rank_vec(ig::IsingGraph) = Int[get_prop((ig), v, :rank) for v ∈ vertices(ig)] basis_size(ig::IsingGraph) = prod(rank_vec(ig)) biases(ig::IsingGraph) = get_prop.(Ref(ig), vertices(ig), :h) -function couplings(ig::IsingGraph) - J = zeros(nv(ig), nv(ig)) +function couplings(ig::IsingGraph{T}) where T + J = zeros(T, nv(ig), nv(ig)) for edge ∈ edges(ig) - i, j = ig.reverse_label_map[src(edge)], ig.reverse_label_map[dst(edge)] + i = ig.reverse_label_map[src(edge)] + j = ig.reverse_label_map[dst(edge)] @inbounds J[i, j] = get_prop(ig, edge, :J) end J @@ -67,11 +70,9 @@ cluster(ig::IsingGraph, verts) = induced_subgraph(ig, collect(verts)) """ Returns dense adjacency matrix between clusters. """ -function inter_cluster_edges(ig::IsingGraph, cl1::IsingGraph, cl2::IsingGraph) - outer_edges = [ - LabelledEdge(i, j) for i ∈ vertices(cl1), j ∈ vertices(cl2) if has_edge(ig, i, j) - ] - J = zeros(nv(cl1), nv(cl2)) +function inter_cluster_edges(ig::IsingGraph{T}, cl1::IsingGraph{T}, cl2::IsingGraph{T}) where T + outer_edges = [LabelledEdge(i, j) for i ∈ vertices(cl1), j ∈ vertices(cl2) if has_edge(ig, i, j)] + J = zeros(T, nv(cl1), nv(cl2)) for e ∈ outer_edges i, j = cl1.reverse_label_map[src(e)], cl2.reverse_label_map[dst(e)] @inbounds J[i, j] = get_prop(ig, e, :J) @@ -83,11 +84,11 @@ end Get rid of non-existing spins. Used only in MPS_search, would be obsolete if MPS_search uses QMps. """ -function prune(ig::IsingGraph) +function prune(ig::IsingGraph; atol::Real=1e-14) to_keep = vcat( findall(!iszero, degree(ig)), findall( - x -> iszero(degree(ig, x)) && !isapprox(get_prop(ig, x, :h), 0, atol=1e-14), + x -> iszero(degree(ig, x)) && !isapprox(get_prop(ig, x, :h), 0, atol=atol), vertices(ig) ) ) diff --git a/src/lattice.jl b/src/lattice.jl index b923784..de4307f 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -8,7 +8,7 @@ export zephyr_lattice_5tuple, zephyr_lattice_5tuple_rotated, periodic_lattice - + "Variable number of Ising graph -> Factor graph coordinate system" function super_square_lattice(size::NTuple{5, Int}) m, um, n, un, t = size @@ -26,21 +26,18 @@ pegasus_lattice(size::NTuple{2, Int}) = pegasus_lattice((size[1], size[2], 3)) function pegasus_lattice(size::NTuple{3, Int}) m, n, t = size # t is number of chimera units old = LinearIndices((1:8*t, 1:n, 1:m)) - map = Dict( - old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4) - ) + map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4)) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 5:8) push!(map, old[k, j, i] => (i, j, 2)) end map end +# TODO masoud / tomek should be removed from function names function pegasus_lattice_masoud(size::NTuple{3, Int}) m, n, t = size # t is number of chimera units old = LinearIndices((1:8*t, 1:n, 1:m)) - map = Dict( - old[k, j, i] => (i, j, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4) - ) + map = Dict(old[k, j, i] => (i, j, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4)) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 5:8) push!(map, old[k, j, i] => (i, j, 1)) end @@ -50,39 +47,32 @@ end function pegasus_lattice_tomek(size::NTuple{3, Int}) m, n, t = size # t is number of chimera units old = LinearIndices((1:8*t, 1:n, 1:m)) - map = Dict( - old[k, j, i] => (i, n-j+1, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4) - ) + map = Dict(old[k, j, i] => (i, n-j+1, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4)) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 5:8) push!(map, old[k, j, i] => (i, n-j+1, 1)) end map end - function zephyr_lattice_z1(size::NTuple{3, Int}) - m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) + m, n, t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) map = Dict{Int, NTuple{3, Int}}() - for i=1:2*n, j in 1:2*m + for i=1:2*n, j ∈ 1:2*m for p in p_func(i, j, t, n, m) - push!(map, (i-1)*(2*n*t) + (j-1)*(2*m*t) + p*n + (i-1)*(j%2) + 1 => (i,j,1)) + push!(map, (i-1)*(2*n*t) + (j-1)*(2*m*t) + p*n + (i-1)*(j%2) + 1 => (i, j, 1)) end - - for q in q_func(i, j, t, n, m) - push!(map, 2*t*(2*n+1) + (i-1)*(2*n*t) + (j%2)*(2*m*t) + q*m + (j-1)*(i-1) + 1 => (i,j,2)) + + for q ∈ q_func(i, j, t, n, m) + push!(map, 2*t*(2*n+1) + (i-1)*(2*n*t) + (j%2)*(2*m*t) + q*m + (j-1)*(i-1) + 1 => (i, j, 2)) end - end map end function j_function(i::Int, n::Int) - if i in collect(1:n) - return collect((n + 1 - i):(n + i)) - else - return collect((i-n):(3*n + 1 - i)) - end + i ∈ collect(1:n) && return collect((n + 1 - i):(n + i)) + collect((i-n):(3*n + 1 - i)) end zephyr_lattice(size::NTuple{2, Int}) = zephyr_lattice((size[1], size[2], 4)) @@ -135,7 +125,6 @@ function rotate(m::Int, n::Int) end end new_dict - end function empty_clusters(m::Int, n::Int) @@ -161,7 +150,7 @@ function zephyr_lattice_5tuple_rotated(m::Int, n::Int, map::Dict{Int, NTuple{3, empty_vertices = empty_indexing(m,n) for (k,l) ∈ enumerate(empty_vertices) push!(new_map, -k => l) - end + end new_map end @@ -170,16 +159,15 @@ function empty_indexing(m::Int, n::Int) p = Int((m-1)/2) empty_vertices = [] for (k,l) ∈ enumerate(ii) - for i in 1:l + for i ∈ 1:l push!(empty_vertices, (k, i, 1)) push!(empty_vertices, (k, i, 2)) push!(empty_vertices, (k, i + m - p + k - 1, 1)) push!(empty_vertices, (k, i + m - p + k - 1, 2)) - end end for (k,l) ∈ enumerate(reverse(ii)) - for i in 1:l + for i ∈ 1:l push!(empty_vertices, (k + m - p, i, 1)) push!(empty_vertices, (k + m - p, i, 2)) push!(empty_vertices, (k + m - p, ii[k] + m - p + k - i, 1)) @@ -193,7 +181,7 @@ function periodic_lattice(size::NTuple{3, Int}) m, n, t = size map = super_square_lattice((m, n, t)) new_map = Dict{Int, NTuple{2, Int}}() - for (key, val) in map + for (key, val) ∈ map i, j = val if i <= m/2 if j <= m/2 @@ -206,8 +194,8 @@ function periodic_lattice(size::NTuple{3, Int}) push!(new_map, key => (m-i+1, j)) elseif j > m/2 push!(new_map, key => (m-i+1, m-j+1)) - end + end end end new_map -end \ No newline at end of file +end diff --git a/src/spectrum.jl b/src/spectrum.jl index b06d520..623bcf2 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -24,11 +24,11 @@ function energy(σ::AbstractArray{State}, ig::IsingGraph) dot.(σ, Ref(J), σ) + dot.(Ref(h), σ) end -function Spectrum(ig::IsingGraph) +function Spectrum(ig::IsingGraph{T}) where T L = nv(ig) N = 2^L - energies = zeros(Float64, N) + energies = zeros(T, N) states = Vector{State}(undef, N) J, h = couplings(ig), biases(ig) @@ -41,7 +41,7 @@ function Spectrum(ig::IsingGraph) end #Only for testing purposes -function gibbs_tensor(ig::IsingGraph, β::Real=1.0) +function gibbs_tensor(ig::IsingGraph, β::Real=1) σ = collect.(all_states(rank_vec(ig))) ρ = exp.(-β .* energy(σ, ig)) ρ ./ sum(ρ) @@ -51,9 +51,9 @@ function brute_force(ig::IsingGraph, s::Symbol=:CPU; num_states::Int=1) brute_force(ig, Val(s); num_states) end -function brute_force(ig::IsingGraph, ::Val{:CPU}; num_states::Int=1) +function brute_force(ig::IsingGraph{T}, ::Val{:CPU}; num_states::Int=1) where T L = nv(ig) - if L == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end + L == 0 && return Spectrum(zeros(T, 1), Vector{Vector{Int}}[]) sp = Spectrum(ig) num_states = min(num_states, prod(rank_vec(ig))) idx = partialsortperm(vec(sp.energies), 1:num_states) @@ -61,8 +61,8 @@ function brute_force(ig::IsingGraph, ::Val{:CPU}; num_states::Int=1) end #TODO: to be removed -function full_spectrum(ig::IsingGraph; num_states::Int=1) - if nv(ig) == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end +function full_spectrum(ig::IsingGraph{T}; num_states::Int=1) where T + nv(ig) == 0 && return Spectrum(zeros(T, 1), Vector{Vector{Int}}[]) ig_rank = rank_vec(ig) num_states = min(num_states, prod(ig_rank)) σ = collect.(all_states(ig_rank)) @@ -71,9 +71,7 @@ function full_spectrum(ig::IsingGraph; num_states::Int=1) end function inter_cluster_energy( - cl1_states::Vector{State}, - J::Matrix{<:Real}, - cl2_states::Vector{State} + cl1_states::Vector{State}, J::Matrix{<:Real}, cl2_states::Vector{State} ) hcat(collect.(cl1_states)...)' * J * hcat(collect.(cl2_states)...) end diff --git a/src/utils.jl b/src/utils.jl index e40d502..226f177 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -7,10 +7,7 @@ m - Grid parameter for the Zephyr lattice. t - Tile parameter for the Zephyr lattice; must be even. """ function zephyr_to_linear(m::Int, t::Int, q::NTuple{5, Int}) - M = 2 * m + 1 u, w, k, j, z = q - ind = (((u * M + w) * t + k) * 2 + j) * m + z + 1 - - ind -end \ No newline at end of file + (((u * M + w) * t + k) * 2 + j) * m + z + 1 +end diff --git a/test/ising.jl b/test/ising.jl index 15933cc..855ebb6 100644 --- a/test/ising.jl +++ b/test/ising.jl @@ -4,57 +4,50 @@ using LabelledGraphs @testset "Ising graph cannot be created" begin @testset "if input instance contains duplicate edges" begin - @test_throws ArgumentError ising_graph( - Dict((1, 1) => 2.0, (1, 2) => 0.5, (2, 1) => -1.0)) + for T ∈ [Float16, Float32, Float64] + @test_throws ArgumentError ising_graph(T, + Dict((1, 1) => 2.0, (1, 2) => 0.5, (2, 1) => -1.0) + ) + end end end -for (instance, source) ∈ ( - ("$(@__DIR__)/instances/example.txt", "file"), - ( - Dict( - (1, 1) => 0.1, - (2, 2) => 0.5, - (1, 4) => -2.0, - (4, 2) => 1.0, - (1, 2) => -0.3 - ), - "array" - ) -) -@testset "Ising graph created from $(source)" begin - expected_num_vertices = 3 - expected_biases = [0.1, 0.5, 0.0] - expected_couplings = Dict( - LabelledEdge(1, 2) => -0.3, - LabelledEdge(1, 4) => -2.0, - LabelledEdge(2, 4) => 1.0 +for T ∈ [Float16, Float32, Float64] + for (instance, source) ∈ ( + ("$(@__DIR__)/instances/example.txt", "file"), + (Dict{Tuple{Int, Int}, T}((1, 1) => 0.1, (2, 2) => 0.5, (1, 4) => -2.0, (4, 2) => 1.0, (1, 2) => -0.3), "array") ) - expected_J_matrix = [[0 -0.3 -2.0]; [0 0 1.0]; [0 0 0]] - - ig = ising_graph(instance) - - @testset "contains the same number vertices as original instance" begin - @test nv(ig) == expected_num_vertices - end - - @testset "has collection of edges comprising all interactions from instance" begin - # This test uses the fact that edges iterates in the lex ordering. - @test collect(edges(ig)) == [LabelledEdge(e...) for e in [(1, 2), (1, 4), (2, 4)]] - end - - @testset "stores biases as property of vertices" begin - @test biases(ig) == expected_biases - end - - @testset "stores couplings both as property of edges and its own property" begin - @test couplings(ig) == expected_J_matrix + @testset "Ising graph created from $(source)" begin + expected_num_vertices = 3 + expected_biases = [T(1/10), T(1/2), T(0)] + expected_couplings = Dict(LabelledEdge(1, 2) => -T(3/10), LabelledEdge(1, 4) => -T(2), LabelledEdge(2, 4) => T(1)) + expected_J_matrix = [[T(0) -T(3/10) -T(2)]; [T(0) T(0) T(1)]; [T(0) T(0) T(0)]] + + ig = ising_graph(T, instance) + @test eltype(ig) == T + + @testset "contains the same number vertices as original instance" begin + @test nv(ig) == expected_num_vertices + end + + @testset "has collection of edges comprising all interactions from instance" begin + # This test uses the fact that edges iterates in the lex ordering. + @test collect(edges(ig)) == [LabelledEdge(e...) for e in [(1, 2), (1, 4), (2, 4)]] + end + + @testset "stores biases as property of vertices" begin + @test biases(ig) == expected_biases + end + + @testset "stores couplings both as property of edges and its own property" begin + @test couplings(ig) == expected_J_matrix + end + + @testset "has default rank stored for each active vertex" begin + @test get_prop(ig, :rank) == Dict(1 => 2, 2 => 2, 4 => 2) + end + end end - - @testset "has default rank stored for each active vertex" begin - @test get_prop(ig, :rank) == Dict(1 => 2, 2 => 2, 4 => 2) - end -end end @testset "Ising graph created with additional parameters" begin diff --git a/test/runtests.jl b/test/runtests.jl index 8e88be1..7a06c56 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -29,8 +29,8 @@ end my_tests = [ "ising.jl", - "factor.jl", - "utils.jl", + #"factor.jl", + #"utils.jl", ] for my_test ∈ my_tests diff --git a/test/utils.jl b/test/utils.jl index 2c2b4c8..b63a2e0 100644 --- a/test/utils.jl +++ b/test/utils.jl @@ -1,78 +1,12 @@ - -# It is posible that more thorough tests will be needed - -@testset verbose = true "Renumeration works like in python" begin - #instance = "$(@__DIR__)/instances/pegasus/2x2x3.txt" - - @testset "linear_to_pegasus" begin - - python_P2_ltp = Dict(0 => (0, 0, 0, 0), 11 => (0, 0, 11, 0), - 18 => (0, 1, 6, 0), 23 => (0, 1, 11, 0)) - - python_P4_ltp = Dict(0 => (0, 0, 0, 0), 86 => (0, 2, 4, 2), - 112 => (0, 3, 1, 1), 215 => (1, 1, 11, 2)) - - python_P8_ltp = Dict(0 => (0, 0, 0, 0), 253 => (0, 3, 0, 1), - 860 => (1, 2, 2, 6), 1175=> (1, 5, 11, 6)) - - python_P16_ltp = Dict(0 => (0, 0, 0, 0), 2530 => (0, 14, 0, 10), - 4860 => (1, 11, 0, 0), 5399 => (1, 13, 11, 14)) - - for i in keys(python_P2_ltp) - @test linear_to_pegasus(2, i) == python_P2_ltp[i] - end - - for i in keys(python_P4_ltp) - @test linear_to_pegasus(4, i) == python_P4_ltp[i] - end - - for i in keys(python_P8_ltp) - @test linear_to_pegasus(8, i) == python_P8_ltp[i] - end - - for i in keys(python_P16_ltp) - @test linear_to_pegasus(16, i) == python_P16_ltp[i] - end - end - - @testset "pegasus_to_nice" begin - - python_ptn = Dict((0,0,4,0) => (0, 0, 0, 0, 0), (0, 3, 1, 1) => (2, 1, 2, 0, 1), - (1, 5, 11, 6) => (2, 5, 6, 1, 3), (1, 14, 0, 10) => (1, 13, 10, 1, 0)) - - for p in keys(python_ptn) - @test pegasus_to_nice(p) == python_ptn[p] - end - end - - @testset "linear_to_nice" begin - @test linear_to_nice(16, 111) == (0, 6, 0, 0, 3) - end - - @testset "nice_to_dattani" begin - @test nice_to_dattani((2, 5, 6, 1, 3)) == (6, 5, 2, 1, 3) - end - - @testset "dattani_to_linear" begin - python_P16_dtl = Dict((12, 7, 1, 1, 0) => 4501, (6, 10, 1, 0, 0) => 2409, - (3, 2, 2, 0, 1) => 1146, (9, 0, 2, 0, 3)=> 3260, (10, 3, 1, 0, 2) => 3683) - for i in keys(python_P16_dtl) - @test dattani_to_linear(16, i) == python_P16_dtl[i] - end - end -end - -# This test takes long time. - @testset verbose = true "Renumerated instances generate correct factor graph" begin instance_dir = "$(@__DIR__)/instances/pegasus/" instances = ["P2", "P4", "P8", "P16"] - size = [2,4,8,16] + size = [2, 4, 8, 16] @testset "$instance" for (i, instance) ∈ enumerate(instances) instance = instance * ".txt" - s = size[i]-1 + s = size[i] - 1 m, n, t = s, s, 24 max_cl_states = 2 @@ -81,14 +15,13 @@ end ig, max_cl_states, spectrum = brute_force, - cluster_assignment_rule=super_square_lattice((m, n, t)) + cluster_assignment_rule = super_square_lattice((m, n, t)) ) - @test nv(fg) == s^2 if s > 1 for l in 1:s-1, k in 2:s - @test has_edge(fg, (l,k), (l+1,k-1)) + @test has_edge(fg, (l, k), (l+1, k-1)) end end end From 1c016c85647d58de579214d4b5878716ce2f3c97 Mon Sep 17 00:00:00 2001 From: Bartek Date: Sat, 25 Feb 2023 13:21:43 +0000 Subject: [PATCH 123/218] clean up tests --- src/factor.jl | 35 +++++---- src/ising.jl | 4 +- test/factor.jl | 186 ++++++++++++++++++++++++----------------------- test/ising.jl | 15 ++-- test/runtests.jl | 6 +- test/utils.jl | 12 ++- 6 files changed, 133 insertions(+), 125 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 23cd9e7..07b69e0 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -7,13 +7,11 @@ export energy, cluster_size -const FactorGraph{T} = LabelledGraph{MetaDiGraph{Int64, T}, Int64} - """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ -function split_into_clusters(ig::IsingGraph, assignment_rule) - cluster_id_to_verts = Dict(i => T[] for i in values(assignment_rule)) +function split_into_clusters(ig::LabelledGraph{G, L}, assignment_rule) where {G, L} + cluster_id_to_verts = Dict(i => L[] for i in values(assignment_rule)) for v in vertices(ig) push!(cluster_id_to_verts[assignment_rule[v]], v) end Dict(i => first(cluster(ig, verts)) for (i, verts) ∈ cluster_id_to_verts) end @@ -23,17 +21,24 @@ Create factor graph. Factor graph order introduced as a natural order in factor graph coordinates. """ function factor_graph( - ig::IsingGraph, num_states_cl::Int; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict -) + ig::IsingGraph, + num_states_cl::Int; + spectrum::Function=full_spectrum, + cluster_assignment_rule::Dict{Int, L} # e.g. square lattice +) where L ns = Dict(i => num_states_cl for i ∈ Set(values(cluster_assignment_rule))) factor_graph(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end function factor_graph( - ig::IsingGraph{T}, num_states_cl::Dict{T, Int}; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict + ig::IsingGraph, + num_states_cl::Dict{T, Int}; + spectrum::Function=full_spectrum, + cluster_assignment_rule::Dict{Int, T} ) where T L = maximum(values(cluster_assignment_rule)) - fg = FactorGraph{T}(sort(unique(values(cluster_assignment_rule)))) + + fg = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) for (v, cl) ∈ split_into_clusters(ig, cluster_assignment_rule) sp = spectrum(cl, num_states=get(num_states_cl, v, basis_size(cl))) @@ -65,7 +70,9 @@ function factor_graph( fg end -function factor_graph(ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict) +function factor_graph( + ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} +) where T factor_graph(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end @@ -82,7 +89,7 @@ Returns Dict(vertex of ising graph -> spin value) Assumes that state has the same order as vertices in factor graph! TODO: check the order consistency over external packages. """ -function decode_factor_graph_state(fg::FactorGraph, state::Vector{Int}) +function decode_factor_graph_state(fg, state::Vector{Int}) ret = Dict{Int, Int}() for (i, vert) ∈ zip(state, vertices(fg)) spins = get_prop(fg, vert, :cluster).labels @@ -113,8 +120,8 @@ function energy(ig::IsingGraph{T}, ig_state::Dict{Int, Int}) where T en end -function energy(fg::FactorGraph{T}, σ::Dict{S, Int}) where {S, T} - en_fg = zero(T) +function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} + en_fg = 0 for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end for edge ∈ edges(fg) pl, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) @@ -124,4 +131,6 @@ function energy(fg::FactorGraph{T}, σ::Dict{S, Int}) where {S, T} en_fg end -cluster_size(fg::FactorGraph, vertex) = length(get_prop(fg, vertex, :spectrum).energies) +function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} + length(get_prop(factor_graph, vertex, :spectrum).energies) +end diff --git a/src/ising.jl b/src/ising.jl index b08659e..c04416e 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -13,14 +13,14 @@ export prune const Instance = Union{String, Dict} -const IsingGraph{T} = LabelledGraph{MetaGraph{Int64, T}} +const IsingGraph{T} = LabelledGraph{MetaGraph{Int, T}} function unique_nodes(ising_tuples) sort(collect(Set(Iterators.flatten((i, j) for (i, j, _) ∈ ising_tuples)))) end """ -Creates Ising graph, H = sgn * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) +Creates Ising graph, convention: H = sgn * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) """ function ising_graph(::Type{T}, inst::Instance; sgn::Real=1, rank_override::Dict=Dict{Int, Int}()) where T # load the Ising instance diff --git a/test/factor.jl b/test/factor.jl index ef11a14..1ec32ef 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -12,27 +12,29 @@ enum(vec) = Dict(v => i for (i, v) ∈ enumerate(vec)) instance = "$(@__DIR__)/instances/chimera_droplets/$(L)power/001.txt" - ig = ising_graph(instance) + for T ∈ [Float16, Float32, Float64] + ig = ising_graph(T, instance) - fg = factor_graph(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t))) + fg = factor_graph(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t))) - @test collect(vertices(fg)) == [(i, j) for i ∈ 1:m for j ∈ 1:n] + @test collect(vertices(fg)) == [(i, j) for i ∈ 1:m for j ∈ 1:n] - clv = [] - cle = [] - rank = rank_vec(ig) + clv = [] + cle = [] + rank = rank_vec(ig) - for v ∈ vertices(fg) - cl = get_prop(fg, v, :cluster) - push!(clv, vertices(cl)) - push!(cle, collect(edges(cl))) + for v ∈ vertices(fg) + cl = get_prop(fg, v, :cluster) + push!(clv, vertices(cl)) + push!(cle, collect(edges(cl))) - @test rank_vec(cl) == get_prop.(Ref(ig), vertices(cl), :rank) - end + @test rank_vec(cl) == get_prop.(Ref(ig), vertices(cl), :rank) + end - # Check if graph is factored correctly - @test isempty(intersect(clv...)) - @test isempty(intersect(cle...)) + # Check if graph is factored correctly + @test isempty(intersect(clv...)) + @test isempty(intersect(cle...)) + end end @testset "Factor graph builds on pathological instance" begin @@ -73,83 +75,81 @@ end ) d = 2 - rank = Dict( - c => fill(d, length(idx)) - for (c,idx) ∈ cells if !isempty(idx) - ) - + rank = Dict(c => fill(d, length(idx)) for (c, idx) ∈ cells if !isempty(idx)) bond_dimensions = [2, 2, 8, 4, 2, 2, 8] - fg = factor_graph( - ising_graph(instance), - spectrum=full_spectrum, - cluster_assignment_rule=super_square_lattice((m, n, t)), - ) - - for (bd, e) in zip(bond_dimensions, edges(fg)) - pl, en, pr = get_prop(fg, e, :pl), get_prop(fg, e, :en), get_prop(fg, e, :pr) - @test minimum(size(en)) == bd - @test maximum(pl) == size(en, 1) - @test maximum(pr) == size(en, 2) - end - - for ((i, j), cedge) ∈ cedges - pl, en, pr = get_prop(fg, i, j, :pl), get_prop(fg, i, j, :en), get_prop(fg, i, j, :pr) - base_i = all_states(rank[i]) - base_j = all_states(rank[j]) - - idx_i = enum(cells[i]) - idx_j = enum(cells[j]) - - # Change it to test if energy is calculated using passed 'energy' function - energy = zeros(prod(rank[i]), prod(rank[j])) - - for (ii, σ) ∈ enumerate(base_i) - for (jj, η) ∈ enumerate(base_j) - eij = 0. - for (k, l) ∈ values(cedge) - kk, ll = enum(cells[i])[k], enum(cells[j])[l] - s, r = σ[idx_i[k]], η[idx_j[l]] - J = couplings[k, l] - eij += s * J * r + for T ∈ [Float16, Float32, Float64] + ig = ising_graph(T, instance) + @test eltype(ig) == T + + fg = factor_graph( + ig, + spectrum=full_spectrum, + cluster_assignment_rule=super_square_lattice((m, n, t)), + ) + + for (bd, e) in zip(bond_dimensions, edges(fg)) + pl, en, pr = get_prop(fg, e, :pl), get_prop(fg, e, :en), get_prop(fg, e, :pr) + @test minimum(size(en)) == bd + @test maximum(pl) == size(en, 1) + @test maximum(pr) == size(en, 2) + end + + for ((i, j), cedge) ∈ cedges + pl, en, pr = get_prop(fg, i, j, :pl), get_prop(fg, i, j, :en), get_prop(fg, i, j, :pr) + base_i = all_states(rank[i]) + base_j = all_states(rank[j]) + + idx_i = enum(cells[i]) + idx_j = enum(cells[j]) + + # Change it to test if energy is calculated using passed 'energy' function + energy = zeros(T, prod(rank[i]), prod(rank[j])) + + for (ii, σ) ∈ enumerate(base_i), (jj, η) ∈ enumerate(base_j) + eij = zero(T) + for (k, l) ∈ values(cedge) + kk = enum(cells[i])[k] + ll = enum(cells[j])[l] + s = σ[idx_i[k]] + r = η[idx_j[l]] + J = couplings[k, l] + eij += s * J * r + end + energy[ii, jj] = eij end - energy[ii, jj] = eij - end - end - @test energy ≈ en[pl, pr] - end - - @testset "each cluster comprises expected cells" begin - for v ∈ vertices(fg) - cl = get_prop(fg, v, :cluster) - - @test issetequal(vertices(cl), cells[v]) - end - end - - @testset "each edge comprises expected bunch of edges from source Ising graph" begin - for e ∈ edges(fg) - outer_edges = get_prop(fg, e, :outer_edges) - - @test issetequal(cedges[(src(e), dst(e))], [(src(oe), dst(oe)) for oe ∈ outer_edges]) - end - end + @test eltype(energy) == T == eltype(en) + @test energy ≈ en[pl, pr] + end + @testset "each cluster comprises expected cells" begin + for v ∈ vertices(fg) + cl = get_prop(fg, v, :cluster) + @test issetequal(vertices(cl), cells[v]) + end + end + @testset "each edge comprises expected bunch of edges from source Ising graph" begin + for e ∈ edges(fg) + outer_edges = get_prop(fg, e, :outer_edges) + @test issetequal(cedges[(src(e), dst(e))], [(src(oe), dst(oe)) for oe ∈ outer_edges]) + end + end + end end -function create_example_factor_graph() - J12 = -1.0 - h1 = 0.5 - h2 = 0.75 +function create_example_factor_graph(::Type{T}) where T + J12 = -1 + h1 = 1/2 + h2 = 0.75 - D = Dict((1, 2) => J12, (1, 1) => h1, (2, 2) => h2) - ig = ising_graph(D) + D = Dict((1, 2) => J12, (1, 1) => h1, (2, 2) => h2) + ig = ising_graph(T, D) - factor_graph( - ig, - Dict((1, 1) => 2, (1, 2) => 2), - spectrum = full_spectrum, - cluster_assignment_rule = Dict(1 => (1, 1), 2 => (1, 2)), - ) + factor_graph( + ig, + Dict((1, 1) => 2, (1, 2) => 2), + spectrum = full_spectrum, + cluster_assignment_rule = Dict(1 => (1, 1), 2 => (1, 2)), + ) end fg_state_to_spin = [ @@ -157,12 +157,16 @@ fg_state_to_spin = [ ] @testset "Decoding solution gives correct spin assignment" begin - fg = create_example_factor_graph() - for (state, spin_values) ∈ fg_state_to_spin - d = decode_factor_graph_state(fg, state) - states = collect(values(d))[collect(keys(d))] - @test states == spin_values - end + + for T ∈ [Float16, Float32, Float64] + fg = create_example_factor_graph(T) + @test all(eltype(get_prop(fg, e, :en)) == T for e ∈ edges(fg)) + for (state, spin_values) ∈ fg_state_to_spin + d = decode_factor_graph_state(fg, state) + states = collect(values(d))[collect(keys(d))] + @test states == spin_values + end + end end """ diff --git a/test/ising.jl b/test/ising.jl index 855ebb6..f49b045 100644 --- a/test/ising.jl +++ b/test/ising.jl @@ -5,8 +5,8 @@ using LabelledGraphs @testset "Ising graph cannot be created" begin @testset "if input instance contains duplicate edges" begin for T ∈ [Float16, Float32, Float64] - @test_throws ArgumentError ising_graph(T, - Dict((1, 1) => 2.0, (1, 2) => 0.5, (2, 1) => -1.0) + @test_throws ArgumentError ising_graph( + T, Dict((1, 1) => 2.0, (1, 2) => 0.5, (2, 1) => -1.0) ) end end @@ -20,29 +20,26 @@ for T ∈ [Float16, Float32, Float64] @testset "Ising graph created from $(source)" begin expected_num_vertices = 3 expected_biases = [T(1/10), T(1/2), T(0)] - expected_couplings = Dict(LabelledEdge(1, 2) => -T(3/10), LabelledEdge(1, 4) => -T(2), LabelledEdge(2, 4) => T(1)) + expected_couplings = Dict( + LabelledEdge(1, 2) => -T(3/10), LabelledEdge(1, 4) => -T(2), LabelledEdge(2, 4) => T(1) + ) expected_J_matrix = [[T(0) -T(3/10) -T(2)]; [T(0) T(0) T(1)]; [T(0) T(0) T(0)]] ig = ising_graph(T, instance) @test eltype(ig) == T - @testset "contains the same number vertices as original instance" begin @test nv(ig) == expected_num_vertices end - @testset "has collection of edges comprising all interactions from instance" begin # This test uses the fact that edges iterates in the lex ordering. - @test collect(edges(ig)) == [LabelledEdge(e...) for e in [(1, 2), (1, 4), (2, 4)]] + @test collect(edges(ig)) == [LabelledEdge(e...) for e ∈ [(1, 2), (1, 4), (2, 4)]] end - @testset "stores biases as property of vertices" begin @test biases(ig) == expected_biases end - @testset "stores couplings both as property of edges and its own property" begin @test couplings(ig) == expected_J_matrix end - @testset "has default rank stored for each active vertex" begin @test get_prop(ig, :rank) == Dict(1 => 2, 2 => 2, 4 => 2) end diff --git a/test/runtests.jl b/test/runtests.jl index 7a06c56..f6dbb91 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -9,7 +9,7 @@ using Test Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) - eng = zeros(1,n) + eng = zeros(1, n) for (i, j) ∈ keys(cedges) for (k, l) ∈ values(cedges[i, j]) for m ∈ 1:length(config[k]) @@ -28,8 +28,8 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) end my_tests = [ - "ising.jl", - #"factor.jl", + #"ising.jl", + "factor.jl", #"utils.jl", ] diff --git a/test/utils.jl b/test/utils.jl index b63a2e0..665d2c9 100644 --- a/test/utils.jl +++ b/test/utils.jl @@ -1,10 +1,10 @@ +instance_dir = "$(@__DIR__)/instances/pegasus/" +instances = ["P2"] #, "P4", "P8", "P16"] + @testset verbose = true "Renumerated instances generate correct factor graph" begin - instance_dir = "$(@__DIR__)/instances/pegasus/" - instances = ["P2", "P4", "P8", "P16"] size = [2, 4, 8, 16] @testset "$instance" for (i, instance) ∈ enumerate(instances) - instance = instance * ".txt" s = size[i] - 1 m, n, t = s, s, 24 @@ -17,12 +17,10 @@ spectrum = brute_force, cluster_assignment_rule = super_square_lattice((m, n, t)) ) - @test nv(fg) == s^2 + @test nv(fg) == s ^ 2 if s > 1 - for l in 1:s-1, k in 2:s - @test has_edge(fg, (l, k), (l+1, k-1)) - end + @test all(has_edge(fg, (l, k), (l+1, k-1)) for l ∈ 1:s-1, k ∈ 2:s) end end end From 0a0b3aa206230cf71a4d3775587c1bc796694dff Mon Sep 17 00:00:00 2001 From: Bartek Date: Sat, 25 Feb 2023 13:55:59 +0000 Subject: [PATCH 124/218] restor tests --- src/SpinGlassNetworks.jl | 1 - src/lattice.jl | 4 ---- src/spectrum.jl | 6 ++---- test/runtests.jl | 4 ++-- 4 files changed, 4 insertions(+), 11 deletions(-) diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 0a0f097..4b94953 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -11,7 +11,6 @@ module SpinGlassNetworks export unique_neighbors - unique_neighbors(ig::LabelledGraph, i::Int) = filter(j -> j > i, neighbors(ig, i)) @generated function unique_dims(A::AbstractArray{T,N}, dim::Integer) where {T,N} diff --git a/src/lattice.jl b/src/lattice.jl index de4307f..5fe4168 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -57,7 +57,6 @@ end function zephyr_lattice_z1(size::NTuple{3, Int}) m, n, t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) map = Dict{Int, NTuple{3, Int}}() - for i=1:2*n, j ∈ 1:2*m for p in p_func(i, j, t, n, m) push!(map, (i-1)*(2*n*t) + (j-1)*(2*m*t) + p*n + (i-1)*(j%2) + 1 => (i, j, 1)) @@ -85,9 +84,7 @@ end function zephyr_lattice_5tuple(size::NTuple{3, Int}) m, n , t = size # t is identical to dwave (Tile parameter for the Zephyr lattice) map = Dict{Int, NTuple{3, Int}}() - # ( u, w, k, ζ, z) - for u = 0 for w ∈ 0:2:2*m, k ∈ 0:t-1, ζ ∈ 0:1, (i,z) ∈ enumerate(0:n-1) push!(map, zephyr_to_linear(m, t, (u,w,k,ζ,z)) => (2*i, w + 1, 1)) @@ -106,7 +103,6 @@ function zephyr_lattice_5tuple(size::NTuple{3, Int}) end end map - end function rotate(m::Int, n::Int) diff --git a/src/spectrum.jl b/src/spectrum.jl index 623bcf2..c644654 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -15,7 +15,7 @@ all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank).. const State = Vector{Int} struct Spectrum - energies::Vector{<:Real} + energies::Vector{T<:Real} states::AbstractArray{State} end @@ -70,8 +70,6 @@ function full_spectrum(ig::IsingGraph{T}; num_states::Int=1) where T Spectrum(energies[begin:num_states], σ[begin:num_states]) end -function inter_cluster_energy( - cl1_states::Vector{State}, J::Matrix{<:Real}, cl2_states::Vector{State} -) +function inter_cluster_energy(cl1_states::Vector{State}, J::Matrix{<:Real}, cl2_states::Vector{State}) hcat(collect.(cl1_states)...)' * J * hcat(collect.(cl2_states)...) end diff --git a/test/runtests.jl b/test/runtests.jl index f6dbb91..348c622 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -28,9 +28,9 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) end my_tests = [ - #"ising.jl", + "ising.jl", "factor.jl", - #"utils.jl", + "utils.jl", ] for my_test ∈ my_tests From c602bed68b17e42d82ece003d358821fa12d9b8c Mon Sep 17 00:00:00 2001 From: Bartek Date: Sat, 25 Feb 2023 14:06:50 +0000 Subject: [PATCH 125/218] fix a bug --- src/factor.jl | 6 ++++-- src/spectrum.jl | 2 +- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 07b69e0..65f72b3 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -76,7 +76,7 @@ function factor_graph( factor_graph(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end -function rank_reveal(energy, order=:PE) +function rank_reveal(energy::Vector{Vector{T}}, order=:PE) where T <: Real @assert order ∈ (:PE, :EP) dim = order == :PE ? 1 : 2 E, idx = unique_dims(energy, dim) @@ -122,7 +122,9 @@ end function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_fg = 0 - for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end + for v ∈ vertices(fg) + en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] + end for edge ∈ edges(fg) pl, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) en = get_prop(fg, edge, :en) diff --git a/src/spectrum.jl b/src/spectrum.jl index c644654..83d89f8 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -15,7 +15,7 @@ all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank).. const State = Vector{Int} struct Spectrum - energies::Vector{T<:Real} + energies::Vector{<:Real} states::AbstractArray{State} end From d7fd942fe33360e05a4ee3ba7a0ce2661edac25e Mon Sep 17 00:00:00 2001 From: Bartek Date: Sat, 25 Feb 2023 14:42:15 +0000 Subject: [PATCH 126/218] clean up - all test pass --- src/factor.jl | 32 ++++++-------------------------- src/ising.jl | 5 +---- src/spectrum.jl | 14 ++++++++++++-- test/factor.jl | 20 ++++++-------------- 4 files changed, 25 insertions(+), 46 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 65f72b3..b40b977 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -36,10 +36,9 @@ function factor_graph( spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} ) where T - L = maximum(values(cluster_assignment_rule)) - - fg = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) - + fg = LabelledGraph{MetaDiGraph}( + sort(unique(values(cluster_assignment_rule))) + ) for (v, cl) ∈ split_into_clusters(ig, cluster_assignment_rule) sp = spectrum(cl, num_states=get(num_states_cl, v, basis_size(cl))) set_props!(fg, v, Dict(:cluster => cl, :spectrum => sp)) @@ -70,9 +69,7 @@ function factor_graph( fg end -function factor_graph( - ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} -) where T +function factor_graph(ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T}) where T factor_graph(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end @@ -102,31 +99,14 @@ function decode_factor_graph_state(fg, state::Vector{Int}) ret end -""" -TODO: write it better (for now this is only for testing). -""" -function energy(ig::IsingGraph{T}, ig_state::Dict{Int, Int}) where T - en = zero(T) - for (i, σ) ∈ ig_state - en += get_prop(ig, i, :h) * σ - for (j, η) ∈ ig_state - if has_edge(ig, i, j) - en += σ * get_prop(ig, i, j, :J) * η / T(2) - elseif has_edge(ig, j, i) - en += σ * get_prop(ig, j, i, :J) * η / T(2) - end - end - end - en -end - function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_fg = 0 for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end for edge ∈ edges(fg) - pl, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) + pl = get_prop(fg, edge, :pl) + pr = get_prop(fg, edge, :pr) en = get_prop(fg, edge, :en) en_fg += en[pl[σ[src(edge)]], pr[σ[dst(edge)]]] end diff --git a/src/ising.jl b/src/ising.jl index c04416e..31b5e08 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -87,10 +87,7 @@ Used only in MPS_search, would be obsolete if MPS_search uses QMps. function prune(ig::IsingGraph; atol::Real=1e-14) to_keep = vcat( findall(!iszero, degree(ig)), - findall( - x -> iszero(degree(ig, x)) && !isapprox(get_prop(ig, x, :h), 0, atol=atol), - vertices(ig) - ) + findall(x -> iszero(degree(ig, x)) && !isapprox(get_prop(ig, x, :h), 0, atol=atol), vertices(ig)) ) gg = ig[ig.labels[to_keep]] labels = collect(vertices(gg.inner_graph)) diff --git a/src/spectrum.jl b/src/spectrum.jl index 83d89f8..c72ee00 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -24,10 +24,21 @@ function energy(σ::AbstractArray{State}, ig::IsingGraph) dot.(σ, Ref(J), σ) + dot.(Ref(h), σ) end +function energy(ig::IsingGraph{T}, ig_state::Dict{Int, Int}) where T + en = zero(T) + for (i, σ) ∈ ig_state + en += get_prop(ig, i, :h) * σ + for (j, η) ∈ ig_state + edge = has_edge(ig, i, j) ? (i, j) : (j, i) + en += T(1/2) * σ * get_prop(ig, edge..., :J) * η + end + end + en +end + function Spectrum(ig::IsingGraph{T}) where T L = nv(ig) N = 2^L - energies = zeros(T, N) states = Vector{State}(undef, N) @@ -40,7 +51,6 @@ function Spectrum(ig::IsingGraph{T}) where T Spectrum(energies, states) end -#Only for testing purposes function gibbs_tensor(ig::IsingGraph, β::Real=1) σ = collect.(all_states(rank_vec(ig))) ρ = exp.(-β .* energy(σ, ig)) diff --git a/test/factor.jl b/test/factor.jl index 1ec32ef..f5c7d5a 100644 --- a/test/factor.jl +++ b/test/factor.jl @@ -152,9 +152,7 @@ function create_example_factor_graph(::Type{T}) where T ) end -fg_state_to_spin = [ - ([1, 1], [-1, -1]), ([1, 2], [-1, 1]), ([2, 1], [1, -1]), ([2, 2], [1, 1]) -] +fg_state_to_spin = [([1, 1], [-1, -1]), ([1, 2], [-1, 1]), ([2, 1], [1, -1]), ([2, 2], [1, 1])] @testset "Decoding solution gives correct spin assignment" begin @@ -204,7 +202,6 @@ function create_larger_example_factor_graph() (3, 6) => 1.1, (6, 9) => 0.7 ) - ig = ising_graph(instance) assignment_rule = Dict( @@ -218,21 +215,19 @@ function create_larger_example_factor_graph() 8 => (2, 1), 9 => (2, 2) ) - fg = factor_graph( ig, Dict{NTuple{2, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule, ) - ig, fg end function factor_graph_energy(fg, state) # This is highly inefficient, but simple, which makes it suitable for testing. # If such a function is needed elsewhere, we need to implement it properly. - total_en = 0.0 + total_en = 0 # Collect local terms from each cluster for (s, v) ∈ zip(state, vertices(fg)) @@ -246,11 +241,9 @@ function factor_graph_energy(fg, state) edge_energy = en[pl, pr] total_en += edge_energy[state[i], state[j]] end - total_en end - @testset "Decoding solution gives spins configuration with corresponding energies" begin ig, fg = create_larger_example_factor_graph() @@ -260,9 +253,8 @@ end for state ∈ all_states d = decode_factor_graph_state(fg, state) spins = zeros(length(d)) - for (k, v) ∈ d - spins[k] = v - end - @test factor_graph_energy(fg, state) ≈ energy([Int.(spins)], ig)[] - end + for (k, v) ∈ d spins[k] = v end + σ = [Int.(spins)] + @test factor_graph_energy(fg, state) ≈ energy(σ, ig)[] + end end From 807a6f22f15582dbad642509d5c37c7efc1dccb1 Mon Sep 17 00:00:00 2001 From: Bartek Date: Sat, 25 Feb 2023 14:47:37 +0000 Subject: [PATCH 127/218] add more tests --- test/ising.jl | 37 +------------------------------------ test/runtests.jl | 1 + test/spectrum.jl | 45 +++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 47 insertions(+), 36 deletions(-) create mode 100644 test/spectrum.jl diff --git a/test/ising.jl b/test/ising.jl index f49b045..ead8d57 100644 --- a/test/ising.jl +++ b/test/ising.jl @@ -78,7 +78,7 @@ end end end -@testset "Ising" begin +@testset "Ising model is correct" begin L = 4 N = L^2 instance = "$(@__DIR__)/instances/$(N)_001.txt" @@ -95,41 +95,6 @@ end end @test B + B' == A - @testset "Naive brute force for +/-1" begin - k = 2^N - sp = brute_force(ig, num_states=k) - - β = rand(Float64) - ρ = gibbs_tensor(ig, β) - - r = exp.(-β .* sp.energies) - R = r ./ sum(r) - - @test size(ρ) == Tuple(fill(2, N)) - @test sum(R) ≈ sum(ρ) ≈ 1 - @test sp.energies ≈ energy(sp.states, ig) - @test [ρ[idx.(σ)...] for σ ∈ sp.states] ≈ R - end - - @testset "Naive brute force for general spins" begin - L = 4 - ig = ising_graph("$(@__DIR__)/instances/$(L)_001.txt") - - set_prop!(ig, :rank, [3, 2, 5, 4]) - rank = get_prop(ig, :rank) - - all = prod(rank) - sp = full_spectrum(ig, num_states=all) - - β = rand(Float64) - ρ = exp.(-β .* sp.energies) - - ϱ = ρ ./ sum(ρ) - ϱ̃ = gibbs_tensor(ig, β) - - @test [ϱ̃[idx.(σ)...] for σ ∈ sp.states] ≈ ϱ - end - @testset "Reading from Dict" begin instance_dict = Dict() ising = CSV.File(instance, types=[Int, Int, Float64], header=0, comment = "#") diff --git a/test/runtests.jl b/test/runtests.jl index 348c622..4411fb4 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -29,6 +29,7 @@ end my_tests = [ "ising.jl", + "spectrum.jl", "factor.jl", "utils.jl", ] diff --git a/test/spectrum.jl b/test/spectrum.jl new file mode 100644 index 0000000..9a0a0e7 --- /dev/null +++ b/test/spectrum.jl @@ -0,0 +1,45 @@ +using CSV +using LinearAlgebra +using LabelledGraphs + +@testset "Spectrum and related properties of the Ising model are correct" begin + L = 4 + N = L^2 + instance = "$(@__DIR__)/instances/$(N)_001.txt" + ig = ising_graph(instance) + + @testset "Naive brute force for +/-1" begin + k = 2^N + sp = brute_force(ig, num_states=k) + + β = rand(Float64) + ρ = gibbs_tensor(ig, β) + + r = exp.(-β .* sp.energies) + R = r ./ sum(r) + + @test size(ρ) == Tuple(fill(2, N)) + @test sum(R) ≈ sum(ρ) ≈ 1 + @test sp.energies ≈ energy(sp.states, ig) + @test [ρ[idx.(σ)...] for σ ∈ sp.states] ≈ R + end + + @testset "Naive brute force for general spins" begin + L = 4 + ig = ising_graph("$(@__DIR__)/instances/$(L)_001.txt") + + set_prop!(ig, :rank, [3, 2, 5, 4]) + rank = get_prop(ig, :rank) + + all = prod(rank) + sp = full_spectrum(ig, num_states=all) + + β = rand(Float64) + ρ = exp.(-β .* sp.energies) + + ϱ = ρ ./ sum(ρ) + ϱ̃ = gibbs_tensor(ig, β) + + @test [ϱ̃[idx.(σ)...] for σ ∈ sp.states] ≈ ϱ + end +end From b860068e9a7c9c766354ecf40343fe27bf1593a6 Mon Sep 17 00:00:00 2001 From: Bartek Date: Sat, 25 Feb 2023 15:43:33 +0000 Subject: [PATCH 128/218] rearange code a bit --- src/SpinGlassNetworks.jl | 76 --------------------------------------- src/spectrum.jl | 12 ++++--- src/utils.jl | 77 +++++++++++++++++++++++++++++++++++++++- test/spectrum.jl | 5 +++ 4 files changed, 89 insertions(+), 81 deletions(-) diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 4b94953..78ebd6c 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -7,82 +7,6 @@ module SpinGlassNetworks using LinearAlgebra, MKL using Base.Cartesian - import Base.Prehashed - - export unique_neighbors - - unique_neighbors(ig::LabelledGraph, i::Int) = filter(j -> j > i, neighbors(ig, i)) - - @generated function unique_dims(A::AbstractArray{T,N}, dim::Integer) where {T,N} - quote - 1 <= dim <= $N || return copy(A) - hashes = zeros(UInt, axes(A, dim)) - - # Compute hash for each row - k = 0 - @nloops $N i A d->(if d == dim; k = i_d; end) begin - @inbounds hashes[k] = hash(hashes[k], hash((@nref $N A i))) - end - - # Collect index of first row for each hash - uniquerow = similar(Array{Int}, axes(A, dim)) - firstrow = Dict{Prehashed,Int}() - for k = axes(A, dim) - uniquerow[k] = get!(firstrow, Prehashed(hashes[k]), k) - end - uniquerows = collect(values(firstrow)) - - # Check for collisions - collided = falses(axes(A, dim)) - @inbounds begin - @nloops $N i A d->(if d == dim - k = i_d - j_d = uniquerow[k] - else - j_d = i_d - end) begin - if (@nref $N A j) != (@nref $N A i) - collided[k] = true - end - end - end - - if any(collided) - nowcollided = similar(BitArray, axes(A, dim)) - while any(collided) - # Collect index of first row for each collided hash - empty!(firstrow) - for j = axes(A, dim) - collided[j] || continue - uniquerow[j] = get!(firstrow, Prehashed(hashes[j]), j) - end - for v ∈ values(firstrow) - push!(uniquerows, v) - end - - # Check for collisions - fill!(nowcollided, false) - @nloops $N i A d->begin - if d == dim - k = i_d - j_d = uniquerow[k] - (!collided[k] || j_d == k) && continue - else - j_d = i_d - end - end begin - if (@nref $N A j) != (@nref $N A i) - nowcollided[k] = true - end - end - (collided, nowcollided) = (nowcollided, collided) - end - end - - (@nref $N A d->d == dim ? sort!(uniquerows) : (axes(A, d))), indexin(uniquerow, uniquerows) - end - end - include("ising.jl") include("spectrum.jl") include("lattice.jl") diff --git a/src/spectrum.jl b/src/spectrum.jl index c72ee00..d3dce7c 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -14,6 +14,7 @@ export all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank)...) const State = Vector{Int} + struct Spectrum energies::Vector{<:Real} states::AbstractArray{State} @@ -29,8 +30,11 @@ function energy(ig::IsingGraph{T}, ig_state::Dict{Int, Int}) where T for (i, σ) ∈ ig_state en += get_prop(ig, i, :h) * σ for (j, η) ∈ ig_state - edge = has_edge(ig, i, j) ? (i, j) : (j, i) - en += T(1/2) * σ * get_prop(ig, edge..., :J) * η + if has_edge(ig, i, j) + en += T(1/2) * σ * get_prop(ig, i, j, :J) * η + elseif has_edge(ig, j, i) + en += T(1/2) * σ * get_prop(ig, j, i, :J) * η + end end end en @@ -51,7 +55,7 @@ function Spectrum(ig::IsingGraph{T}) where T Spectrum(energies, states) end -function gibbs_tensor(ig::IsingGraph, β::Real=1) +function gibbs_tensor(ig::IsingGraph{T}, β::T=1) where T σ = collect.(all_states(rank_vec(ig))) ρ = exp.(-β .* energy(σ, ig)) ρ ./ sum(ρ) @@ -61,6 +65,7 @@ function brute_force(ig::IsingGraph, s::Symbol=:CPU; num_states::Int=1) brute_force(ig, Val(s); num_states) end +#TODO only one of brute_force and full_spectrum should remain function brute_force(ig::IsingGraph{T}, ::Val{:CPU}; num_states::Int=1) where T L = nv(ig) L == 0 && return Spectrum(zeros(T, 1), Vector{Vector{Int}}[]) @@ -70,7 +75,6 @@ function brute_force(ig::IsingGraph{T}, ::Val{:CPU}; num_states::Int=1) where T Spectrum(sp.energies[idx], sp.states[idx]) end -#TODO: to be removed function full_spectrum(ig::IsingGraph{T}; num_states::Int=1) where T nv(ig) == 0 && return Spectrum(zeros(T, 1), Vector{Vector{Int}}[]) ig_rank = rank_vec(ig) diff --git a/src/utils.jl b/src/utils.jl index 226f177..0f6cf27 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -1,5 +1,8 @@ export - zephyr_to_linear + zephyr_to_linear, + unique_neighbors + +import Base.Prehashed """ Rewriten from Dwave-networkx @@ -11,3 +14,75 @@ function zephyr_to_linear(m::Int, t::Int, q::NTuple{5, Int}) u, w, k, j, z = q (((u * M + w) * t + k) * 2 + j) * m + z + 1 end + +unique_neighbors(ig::LabelledGraph, i::Int) = filter(j -> j > i, neighbors(ig, i)) + +@generated function unique_dims(A::AbstractArray{T,N}, dim::Integer) where {T,N} + quote + 1 <= dim <= $N || return copy(A) + hashes = zeros(UInt, axes(A, dim)) + + # Compute hash for each row + k = 0 + @nloops $N i A d->(if d == dim; k = i_d; end) begin + @inbounds hashes[k] = hash(hashes[k], hash((@nref $N A i))) + end + + # Collect index of first row for each hash + uniquerow = similar(Array{Int}, axes(A, dim)) + firstrow = Dict{Prehashed,Int}() + for k = axes(A, dim) + uniquerow[k] = get!(firstrow, Prehashed(hashes[k]), k) + end + uniquerows = collect(values(firstrow)) + + # Check for collisions + collided = falses(axes(A, dim)) + @inbounds begin + @nloops $N i A d->(if d == dim + k = i_d + j_d = uniquerow[k] + else + j_d = i_d + end) begin + if (@nref $N A j) != (@nref $N A i) + collided[k] = true + end + end + end + + if any(collided) + nowcollided = similar(BitArray, axes(A, dim)) + while any(collided) + # Collect index of first row for each collided hash + empty!(firstrow) + for j = axes(A, dim) + collided[j] || continue + uniquerow[j] = get!(firstrow, Prehashed(hashes[j]), j) + end + for v ∈ values(firstrow) + push!(uniquerows, v) + end + + # Check for collisions + fill!(nowcollided, false) + @nloops $N i A d->begin + if d == dim + k = i_d + j_d = uniquerow[k] + (!collided[k] || j_d == k) && continue + else + j_d = i_d + end + end begin + if (@nref $N A j) != (@nref $N A i) + nowcollided[k] = true + end + end + (collided, nowcollided) = (nowcollided, collided) + end + end + + (@nref $N A d->d == dim ? sort!(uniquerows) : (axes(A, d))), indexin(uniquerow, uniquerows) + end +end diff --git a/test/spectrum.jl b/test/spectrum.jl index 9a0a0e7..72992e9 100644 --- a/test/spectrum.jl +++ b/test/spectrum.jl @@ -22,6 +22,11 @@ using LabelledGraphs @test sum(R) ≈ sum(ρ) ≈ 1 @test sp.energies ≈ energy(sp.states, ig) @test [ρ[idx.(σ)...] for σ ∈ sp.states] ≈ R + + for (i, state) in enumerate(sp.states) + state_dict = Dict(i => s for (i, s) ∈ enumerate(state)) + energy(ig, state_dict) ≈ sp.energies[i] + end end @testset "Naive brute force for general spins" begin From 1adc7a269d993185975338d31c956de610c51ce2 Mon Sep 17 00:00:00 2001 From: Bartek Date: Sat, 25 Feb 2023 16:21:29 +0000 Subject: [PATCH 129/218] final clean up --- src/SpinGlassNetworks.jl | 2 +- src/ising.jl | 11 +++++------ src/lattice.jl | 30 +++++++++++++++++------------- test/ising.jl | 2 +- 4 files changed, 24 insertions(+), 21 deletions(-) diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 78ebd6c..0c6b11e 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -1,7 +1,7 @@ module SpinGlassNetworks using LabelledGraphs using LightGraphs - using MetaGraphs # TODO: remove that + using MetaGraphs # TODO: to be replaced by MetaGraphsNext using CSV using DocStringExtensions using LinearAlgebra, MKL diff --git a/src/ising.jl b/src/ising.jl index 31b5e08..7ad2f0f 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -20,10 +20,9 @@ function unique_nodes(ising_tuples) end """ -Creates Ising graph, convention: H = sgn * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) +Creates Ising graph, convention: H = scale * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) """ -function ising_graph(::Type{T}, inst::Instance; sgn::Real=1, rank_override::Dict=Dict{Int, Int}()) where T - # load the Ising instance +function ising_graph(::Type{T}, inst::Instance; scale::Real=1, rank_override::Dict=Dict{Int, Int}()) where T if inst isa String ising = CSV.File(inst, types = [Int, Int, T], header=0, comment = "#") else @@ -35,7 +34,7 @@ function ising_graph(::Type{T}, inst::Instance; sgn::Real=1, rank_override::Dict foreach(v -> set_prop!(ig, v, :rank, get(rank_override, v, 2)), vertices(ig)) for (i, j, v) ∈ ising - v *= sgn + v *= T(scale) if i == j set_prop!(ig, i, :h, v) else @@ -47,8 +46,8 @@ function ising_graph(::Type{T}, inst::Instance; sgn::Real=1, rank_override::Dict ig end -function ising_graph(inst::Instance; sgn::Real=1, rank_override::Dict=Dict{Int, Int}()) - ising_graph(Float64, inst; sgn = sgn, rank_override = rank_override) +function ising_graph(inst::Instance; scale::Real=1, rank_override::Dict=Dict{Int, Int}()) + ising_graph(Float64, inst; scale = scale, rank_override = rank_override) end Base.eltype(ig::IsingGraph{T}) where T = T diff --git a/src/lattice.jl b/src/lattice.jl index 5fe4168..82b09f0 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -24,9 +24,11 @@ end pegasus_lattice(size::NTuple{2, Int}) = pegasus_lattice((size[1], size[2], 3)) function pegasus_lattice(size::NTuple{3, Int}) - m, n, t = size # t is number of chimera units + m, n, t = size old = LinearIndices((1:8*t, 1:n, 1:m)) - map = Dict(old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4)) + map = Dict( + old[k, j, i] => (i, j, 1) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4) + ) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 5:8) push!(map, old[k, j, i] => (i, j, 2)) end @@ -35,9 +37,11 @@ end # TODO masoud / tomek should be removed from function names function pegasus_lattice_masoud(size::NTuple{3, Int}) - m, n, t = size # t is number of chimera units + m, n, t = size old = LinearIndices((1:8*t, 1:n, 1:m)) - map = Dict(old[k, j, i] => (i, j, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4)) + map = Dict( + old[k, j, i] => (i, j, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4) + ) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 5:8) push!(map, old[k, j, i] => (i, j, 1)) end @@ -45,9 +49,11 @@ function pegasus_lattice_masoud(size::NTuple{3, Int}) end function pegasus_lattice_tomek(size::NTuple{3, Int}) - m, n, t = size # t is number of chimera units + m, n, t = size old = LinearIndices((1:8*t, 1:n, 1:m)) - map = Dict(old[k, j, i] => (i, n-j+1, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4)) + map = Dict( + old[k, j, i] => (i, n-j+1, 2) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 1:4) + ) for i=1:m, j=1:n, k ∈ (p * 8 + q for p ∈ 0 : t-1, q ∈ 5:8) push!(map, old[k, j, i] => (i, n-j+1, 1)) end @@ -107,14 +113,14 @@ end function rotate(m::Int, n::Int) new_dict = Dict{NTuple{3, Int}, NTuple{3, Int}}() - for (k,j) ∈ enumerate(1:2:m) + for (k, j) ∈ enumerate(1:2:m) for (l,i) ∈ enumerate(n-1:-2:1) push!(new_dict, (i,j,1) => (i/2 + k - 1, l + k - 1, 1)) push!(new_dict, (i,j,2) => (i/2 + k - 1, l + k - 1, 2)) end end - for (k,j) ∈ enumerate(2:2:m) + for (k, j) ∈ enumerate(2:2:m) for (l,i) ∈ enumerate(n:-2:1) push!(new_dict, (i,j,1) => ((i-1)/2 + k, l + k - 1, 1)) push!(new_dict, (i,j,2) => ((i-1)/2 + k, l + k - 1, 2)) @@ -125,8 +131,7 @@ end function empty_clusters(m::Int, n::Int) p = (m - 1) / 2 - count = 0 - ii = [] + count, ii = 0, [] for (i, j) ∈ enumerate(1:p-1) count += i push!(ii, i) @@ -135,9 +140,8 @@ function empty_clusters(m::Int, n::Int) end function zephyr_lattice_5tuple_rotated(m::Int, n::Int, map::Dict{Int, NTuple{3, Int}}) - rotated_map = rotate(m, n) #5, 5, for Z2 + rotated_map = rotate(m, n) new_map = Dict{Int, NTuple{3, Int}}() - (empty, ii) = empty_clusters(m, n) for k in keys(map) push!(new_map, k => rotated_map[map[k]]) @@ -154,7 +158,7 @@ function empty_indexing(m::Int, n::Int) (empty, ii) = empty_clusters(m, n) p = Int((m-1)/2) empty_vertices = [] - for (k,l) ∈ enumerate(ii) + for (k, l) ∈ enumerate(ii) for i ∈ 1:l push!(empty_vertices, (k, i, 1)) push!(empty_vertices, (k, i, 2)) diff --git a/test/ising.jl b/test/ising.jl index ead8d57..439d273 100644 --- a/test/ising.jl +++ b/test/ising.jl @@ -62,7 +62,7 @@ end ig = ising_graph( "$(@__DIR__)/instances/example.txt", - sgn=-1, + scale=-1, rank_override=Dict(1 => 3, 4 => 4) ) From e8f5882cc277abf7566689d8c1b0f4e5b3ed5548 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 12 May 2023 15:46:47 +0200 Subject: [PATCH 130/218] add truncated factor graph --- src/factor.jl | 59 ++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 58 insertions(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 5459199..84065b9 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -5,7 +5,8 @@ export split_into_clusters, decode_factor_graph_state, energy, - cluster_size + cluster_size, + truncate_factor_graph """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) @@ -137,3 +138,59 @@ end function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} length(get_prop(factor_graph, vertex, :spectrum).energies) end + +function truncate_factor_graph(fg::LabelledGraph{S, T}, beta::Real, num_states::Int) where {S, T} + states = Dict() + for node in vertices(fg) + E = copy(get_prop(fg, node, :spectrum).energies) + for n in vertices(fg) + if has_edge(fg, node, n) + E_bond = get_prop(fg, node, n, :en) + pl, pr = get_prop(fg, node, n, :pl), get_prop(fg, node, n, :pr) + E_bond = E_bond[pl, pr] + E_neighbor = get_prop(fg, n, :spectrum).energies + E_bond = E_bond .+ reshape(E_neighbor, (1, :)) + E .+= log.(sum(exp.(-E_bond * beta), dims=2))./(-beta) + elseif has_edge(fg, n, node) + E_bond = get_prop(fg, n, node, :en) + pl, pr = get_prop(fg, n, node, :pl), get_prop(fg, n, node, :pr) + E_bond = E_bond[pl, pr]' + E_neighbor = get_prop(fg, n, :spectrum).energies + E_bond = E_bond .+ reshape(E_neighbor, (1, :)) + E .+= log.(sum(exp.(-E_bond * beta), dims=2))./(-beta) + end + end + push!(states, node => sortperm(E)[1:min(num_states, length(E))]) + end + + + new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) + + for v ∈ vertices(new_fg) + cl = get_prop(fg, v, :cluster) + sp = get_prop(fg, v, :spectrum) + sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) + set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) + end + + for e ∈ edges(fg) + v, w = src(e), dst(e) + add_edge!(new_fg, v, w) + outer_edges = get_prop(fg, v, w, :outer_edges) + pl = get_prop(fg, v, w, :pl) + pr = get_prop(fg, v, w, :pr) + en = get_prop(fg, v, w, :en) + pl = pl[states[v]] + pr = pr[states[w]] + pl_transition, pl_unique = rank_reveal(pl, :PE) + pr_transition, pr_unique = rank_reveal(pr, :PE) + en = en[pl_unique[pl_transition], pr_unique[pr_transition]] + + set_props!( + new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) + ) + end + + new_fg + +end \ No newline at end of file From 8c120d3ba9b5f3798d348b7a755b94740b5b006e Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 17 May 2023 11:49:35 +0200 Subject: [PATCH 131/218] truncate factor graph another method --- src/factor.jl | 69 +++++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 67 insertions(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 84065b9..2c9ee7d 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -139,7 +139,7 @@ function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} length(get_prop(factor_graph, vertex, :spectrum).energies) end -function truncate_factor_graph(fg::LabelledGraph{S, T}, beta::Real, num_states::Int) where {S, T} +function truncate_factor_graph(fg::LabelledGraph{S, T}, beta::Real, num_states::Int, ::Val{:mean_field}) where {S, T} states = Dict() for node in vertices(fg) E = copy(get_prop(fg, node, :spectrum).energies) @@ -190,7 +190,72 @@ function truncate_factor_graph(fg::LabelledGraph{S, T}, beta::Real, num_states:: new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) ) end - new_fg +end + +function truncate_factor_graph(fg::LabelledGraph{S, T}, β::Real, num_states::Int, ::Val{:pegasus}) where {S, T} + states = Dict() + for node in vertices(fg) + if node in keys(states) continue end + i, j, _ = node + E1 = copy(get_prop(fg, (i, j, 1), :spectrum).energies) + E2 = copy(get_prop(fg, (i, j, 2), :spectrum).energies) + if has_edge(fg, (i, j, 1), (i, j, 2)) + en12 = copy(get_prop(fg, (i, j, 1), (i, j, 2), :en)) + pl = copy(get_prop(fg, (i, j, 1), (i, j, 2), :pl)) + pr = copy(get_prop(fg, (i, j, 1), (i, j, 2), :pr)) + int_eng = en12[pl, pr] + elseif has_edge(fg, (i, j, 2), (i, j, 1)) + en21 = copy(get_prop(fg, (i, j, 2), (i, j, 1), :en)) + pl = copy(get_prop(fg, (i, j, 2), (i, j, 1), :pl)) + pr = copy(get_prop(fg, (i, j, 2), (i, j, 1), :pr)) + int_eng = en21[pl, pr]' + else + int_eng = zeros(1, 1) + end + E = int_eng .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) + sx, sy = size(E) + E = reshape(E, sx * sy) + ind = sortperm(E)[1:min(num_states, length(E))] + ind1 = mod.(ind .- 1, sx) .+ 1 + ind2 = div.(ind .- 1, sx) .+ 1 + ind1 = sort([Set(ind1)...]) + ind2 = sort([Set(ind2)...]) + push!(states, (i, j, 1) => ind1) + push!(states, (i, j, 2) => ind2) + end + + new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) + # sp = empty_spectrum(num_states) + for v ∈ vertices(new_fg) + cl = get_prop(fg, v, :cluster) + sp = get_prop(fg, v, :spectrum) + if sp.states == Vector{Int64}[] + sp = Spectrum(sp.energies[states[v]], []) + else + sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) + end + set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) + end + + for e ∈ edges(fg) + v, w = src(e), dst(e) + add_edge!(new_fg, v, w) + outer_edges = get_prop(fg, v, w, :outer_edges) + pl = get_prop(fg, v, w, :pl) + pr = get_prop(fg, v, w, :pr) + en = get_prop(fg, v, w, :en) + pl = pl[states[v]] + pr = pr[states[w]] + pl_transition, pl_unique = rank_reveal(pl, :PE) + pr_transition, pr_unique = rank_reveal(pr, :PE) + en = en[pl_unique[pl_transition], pr_unique[pr_transition]] + + set_props!( + new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) + ) + end + + new_fg end \ No newline at end of file From e785fccbb2790fbb5d66d0d80e8ae0f42e618706 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 19 May 2023 11:08:43 +0200 Subject: [PATCH 132/218] fix bug in truncate_factor_graph --- src/factor.jl | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 2c9ee7d..0a82b24 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -139,7 +139,7 @@ function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} length(get_prop(factor_graph, vertex, :spectrum).energies) end -function truncate_factor_graph(fg::LabelledGraph{S, T}, beta::Real, num_states::Int, ::Val{:mean_field}) where {S, T} +function truncate_factor_graph_1site_meanfield(fg::LabelledGraph{S, T}, beta::Real, num_states::Int) where {S, T} states = Dict() for node in vertices(fg) E = copy(get_prop(fg, node, :spectrum).energies) @@ -155,14 +155,14 @@ function truncate_factor_graph(fg::LabelledGraph{S, T}, beta::Real, num_states:: E_bond = get_prop(fg, n, node, :en) pl, pr = get_prop(fg, n, node, :pl), get_prop(fg, n, node, :pr) E_bond = E_bond[pl, pr]' - E_neighbor = get_prop(fg, n, :spectrum).energies + E_neighbor = get_prop(fg, n, :spectrum).energies E_bond = E_bond .+ reshape(E_neighbor, (1, :)) - E .+= log.(sum(exp.(-E_bond * beta), dims=2))./(-beta) + E .+= log.(sum(exp.(-E_bond * beta), dims=2))./(-beta) end end push!(states, node => sortperm(E)[1:min(num_states, length(E))]) end - + new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) @@ -184,7 +184,7 @@ function truncate_factor_graph(fg::LabelledGraph{S, T}, beta::Real, num_states:: pr = pr[states[w]] pl_transition, pl_unique = rank_reveal(pl, :PE) pr_transition, pr_unique = rank_reveal(pr, :PE) - en = en[pl_unique[pl_transition], pr_unique[pr_transition]] + en = en[pl_unique, pr_unique] set_props!( new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) @@ -193,7 +193,7 @@ function truncate_factor_graph(fg::LabelledGraph{S, T}, beta::Real, num_states:: new_fg end -function truncate_factor_graph(fg::LabelledGraph{S, T}, β::Real, num_states::Int, ::Val{:pegasus}) where {S, T} +function truncate_factor_graph_2site(fg::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 states = Dict() for node in vertices(fg) if node in keys(states) continue end @@ -218,7 +218,7 @@ function truncate_factor_graph(fg::LabelledGraph{S, T}, β::Real, num_states::In E = reshape(E, sx * sy) ind = sortperm(E)[1:min(num_states, length(E))] ind1 = mod.(ind .- 1, sx) .+ 1 - ind2 = div.(ind .- 1, sx) .+ 1 + ind2 = div.(ind .- 1, sx) .+ 1 ind1 = sort([Set(ind1)...]) ind2 = sort([Set(ind2)...]) push!(states, (i, j, 1) => ind1) @@ -250,7 +250,7 @@ function truncate_factor_graph(fg::LabelledGraph{S, T}, β::Real, num_states::In pr = pr[states[w]] pl_transition, pl_unique = rank_reveal(pl, :PE) pr_transition, pr_unique = rank_reveal(pr, :PE) - en = en[pl_unique[pl_transition], pr_unique[pr_transition]] + en = en[pl_unique, pr_unique] set_props!( new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) From 75c64752c0786fb9b3442445869d9a47820e2556 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 19 May 2023 11:14:11 +0200 Subject: [PATCH 133/218] fix export truncate_factor_graph --- src/factor.jl | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 0a82b24..e964e01 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -6,7 +6,9 @@ export decode_factor_graph_state, energy, cluster_size, - truncate_factor_graph + truncate_factor_graph_2site, + truncate_factor_graph_1site_meanfield + """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) From b8c0c03938180586c80b1cb894d1eb86441d2d6f Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 19 May 2023 11:58:04 +0200 Subject: [PATCH 134/218] truncate_factor_graph partialsortperm --- src/factor.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index e964e01..224d482 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -162,7 +162,7 @@ function truncate_factor_graph_1site_meanfield(fg::LabelledGraph{S, T}, beta::Re E .+= log.(sum(exp.(-E_bond * beta), dims=2))./(-beta) end end - push!(states, node => sortperm(E)[1:min(num_states, length(E))]) + push!(states, node => partialsortperm(E, 1:min(num_states, length(E)))) end @@ -218,7 +218,7 @@ function truncate_factor_graph_2site(fg::LabelledGraph{S, T}, num_states::Int) w E = int_eng .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) sx, sy = size(E) E = reshape(E, sx * sy) - ind = sortperm(E)[1:min(num_states, length(E))] + ind = partialsortperm(E, 1:min(num_states, length(E))) ind1 = mod.(ind .- 1, sx) .+ 1 ind2 = div.(ind .- 1, sx) .+ 1 ind1 = sort([Set(ind1)...]) From 05945cf687bac1b47f90ab7366a50568e837e391 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 2 Jun 2023 12:07:59 +0200 Subject: [PATCH 135/218] precise truncate --- src/factor.jl | 35 ++++++++++++++++++++++++++++------- 1 file changed, 28 insertions(+), 7 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 224d482..79af17a 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -6,7 +6,8 @@ export decode_factor_graph_state, energy, cluster_size, - truncate_factor_graph_2site, + # truncate_factor_graph_2site, + truncate_factor_graph_2site_precise, truncate_factor_graph_1site_meanfield @@ -195,7 +196,7 @@ function truncate_factor_graph_1site_meanfield(fg::LabelledGraph{S, T}, beta::Re new_fg end -function truncate_factor_graph_2site(fg::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 +function truncate_factor_graph_2site_precise(fg::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 states = Dict() for node in vertices(fg) if node in keys(states) continue end @@ -218,11 +219,7 @@ function truncate_factor_graph_2site(fg::LabelledGraph{S, T}, num_states::Int) w E = int_eng .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) sx, sy = size(E) E = reshape(E, sx * sy) - ind = partialsortperm(E, 1:min(num_states, length(E))) - ind1 = mod.(ind .- 1, sx) .+ 1 - ind2 = div.(ind .- 1, sx) .+ 1 - ind1 = sort([Set(ind1)...]) - ind2 = sort([Set(ind2)...]) + ind1, ind2 = select_numstate_best(E, sx, num_states) push!(states, (i, j, 1) => ind1) push!(states, (i, j, 2) => ind2) end @@ -260,4 +257,28 @@ function truncate_factor_graph_2site(fg::LabelledGraph{S, T}, num_states::Int) w end new_fg +end + + +# truncate based on energy in two nods of factor graph; resulting states are a product of states in two nodes, so we have to fine-tune to end up with expected number of states +function select_numstate_best(E, sx, num_states) + + low, high = 1, min(num_states, length(E)) + + while true + guess = div(low + high, 2) + ind = partialsortperm(E, 1:guess) + ind1 = mod.(ind .- 1, sx) .+ 1 + ind2 = div.(ind .- 1, sx) .+ 1 + ind1 = sort([Set(ind1)...]) + ind2 = sort([Set(ind2)...]) + if high - low <= 2 + return ind1, ind2 + end + if length(ind1) * length(ind2) > num_states + high = guess + else + low = guess + end + end end \ No newline at end of file From dadd178b850dd1843b0d6081fdb5ae3d6f9a5ef6 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 2 Jun 2023 12:45:33 +0200 Subject: [PATCH 136/218] fix truncate factor --- src/factor.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 79af17a..200e120 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -272,7 +272,7 @@ function select_numstate_best(E, sx, num_states) ind2 = div.(ind .- 1, sx) .+ 1 ind1 = sort([Set(ind1)...]) ind2 = sort([Set(ind2)...]) - if high - low <= 2 + if high - low <= 1 return ind1, ind2 end if length(ind1) * length(ind2) > num_states From e1d14b17d0c9bc556687bf4057b746668bf0296d Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Fri, 16 Jun 2023 09:28:00 +0200 Subject: [PATCH 137/218] repaired test of renumerations --- test/utils.jl | 58 +++++++++++++++++++++++++-------------------------- 1 file changed, 29 insertions(+), 29 deletions(-) diff --git a/test/utils.jl b/test/utils.jl index 2c2b4c8..86766aa 100644 --- a/test/utils.jl +++ b/test/utils.jl @@ -64,32 +64,32 @@ end # This test takes long time. -@testset verbose = true "Renumerated instances generate correct factor graph" begin - instance_dir = "$(@__DIR__)/instances/pegasus/" - instances = ["P2", "P4", "P8", "P16"] - size = [2,4,8,16] - - @testset "$instance" for (i, instance) ∈ enumerate(instances) - - instance = instance * ".txt" - s = size[i]-1 - m, n, t = s, s, 24 - max_cl_states = 2 - - ig = ising_graph(joinpath(instance_dir, instance)) - fg = factor_graph( - ig, - max_cl_states, - spectrum = brute_force, - cluster_assignment_rule=super_square_lattice((m, n, t)) - ) - - @test nv(fg) == s^2 - - if s > 1 - for l in 1:s-1, k in 2:s - @test has_edge(fg, (l,k), (l+1,k-1)) - end - end - end -end +# @testset verbose = true "Renumerated instances generate correct factor graph" begin +# instance_dir = "$(@__DIR__)/instances/pegasus/" +# instances = ["P2", "P4", "P8", "P16"] +# size = [2,4,8,16] + +# @testset "$instance" for (i, instance) ∈ enumerate(instances) + +# instance = instance * ".txt" +# s = size[i]-1 +# m, n, t = s, s, 24 +# max_cl_states = 2 + +# ig = ising_graph(joinpath(instance_dir, instance)) +# fg = factor_graph( +# ig, +# max_cl_states, +# spectrum = brute_force, +# cluster_assignment_rule=super_square_lattice((m, n, t)) +# ) + +# @test nv(fg) == s^2 + +# if s > 1 +# for l in 1:s-1, k in 2:s +# @test has_edge(fg, (l,k), (l+1,k-1)) +# end +# end +# end +# end From 89fc0c34d5b57b2e209fdbcecbe947612ac96153 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Mon, 3 Jul 2023 15:21:31 +0200 Subject: [PATCH 138/218] Truncate factor graph based on belief propagation --- src/factor.jl | 144 ++++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 141 insertions(+), 3 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 200e120..a97a9ce 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -8,9 +8,8 @@ export cluster_size, # truncate_factor_graph_2site, truncate_factor_graph_2site_precise, - truncate_factor_graph_1site_meanfield - - + truncate_factor_graph_1site_meanfield, + truncate_factor_graph_belief_propagation """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ @@ -281,4 +280,143 @@ function select_numstate_best(E, sx, num_states) low = guess end end +end + +function get_neighbors(graph::LabelledGraph{S, T}, vertex::Tuple{Any, Any, Any}) where {S, T} + neighbors = [] + for edge in edges(graph) + src_node, dst_node = src(edge), dst(edge) + if src_node == vertex + push!(neighbors, dst_node) + elseif dst_node == vertex + push!(neighbors, src_node) + end + end + return neighbors +end + +# Works for Pegasus and Zephyr +function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta::Real, num_states::Int) where {S, T} + states = Dict() + messages = Dict{Tuple{Any, Any}, Array{Any}}() + beliefs = Dict{Tuple{Any, Any, Any}, Array{Any}}() + + # Initialize messages with uniform probabilities + for v in vertices(fg) + ns = length(get_prop(fg, v, :spectrum).states) + belief = ones(ns)/ns + push!(beliefs, v => belief) + + for neighbor in get_neighbors(fg, v) + if has_edge(fg, v, neighbor) + pl, pr = get_prop(fg, v, neighbor, :pl), get_prop(fg, v, neighbor, :pr) + message_av = ones(ns)/ns + message_va = ones(ns)/ns + push!(messages, (v, (v, neighbor)) => message_va) + push!(messages, ((v, neighbor), v) => message_av) + elseif has_edge(fg, neighbor, v) + pl, pr = get_prop(fg, neighbor, v, :pl), get_prop(fg, neighbor, v, :pr) + message_av = ones(ns)/ns + message_va = ones(ns)/ns + push!(messages, (v, (neighbor, v)) => message_va) + push!(messages, ((neighbor, v), v) => message_av) + end + end + end + + # Perform message passing until convergence + converged = false + iteration = 0 + while !converged && iteration < 100 # Set an appropriate number of iterations and convergence threshold + iteration += 1 + println("iteration", iteration) + old_beliefs = beliefs + for v in vertices(fg) + println("v", v) + for neighbor in get_neighbors(fg, v) + println("neighbor", neighbor) + #update messages + if has_edge(fg, v, neighbor) + messages[(neighbor, (v, neighbor))] = beliefs[neighbor]./messages[(v, neighbor), neighbor] + messages[((v, neighbor), v)] = compute_factor(fg, v, neighbor, beta) * messages[(neighbor, (v, neighbor))] + elseif has_edge(fg, neighbor, v) + messages[(neighbor, (neighbor, v))] = beliefs[neighbor]./messages[(neighbor, v), neighbor] + messages[((neighbor, v), v)] = compute_factor(fg, neighbor, v, beta)' * messages[(neighbor, (neighbor, v))] + end + end + end + for v in vertices(fg) + E_local = get_prop(fg, v, :spectrum).energies + messages_product = E_local./sum(E_local) + for neighbor in get_neighbors(fg, v) + #update beliefs + if has_edge(fg, v, neighbor) + messages_product .*= messages[((v, neighbor), v)] + elseif has_edge(fg, neighbor, v) + messages_product .*= messages[((neighbor, v), v)] + end + end + beliefs[v] = messages_product + # Normalize the beliefs + beliefs[v] ./= sum(beliefs[v]) + end + # Check convergence + if all([all(abs.(old_beliefs[v] .- beliefs[v]) .< 1e-6) for v in keys(beliefs)]) + converged = true + end + end + + # Truncate the state space based on the belief probabilities + for node in vertices(fg) + indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node]))) + push!(states, node => indices) + end + + # Create a new factor graph with truncated state space + new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) + + for v ∈ vertices(new_fg) + cl = get_prop(fg, v, :cluster) + sp = get_prop(fg, v, :spectrum) + sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) + set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) + end + + for e ∈ edges(fg) + v, w = src(e), dst(e) + add_edge!(new_fg, v, w) + outer_edges = get_prop(fg, v, w, :outer_edges) + pl = get_prop(fg, v, w, :pl) + pr = get_prop(fg, v, w, :pr) + en = get_prop(fg, v, w, :en) + pl = pl[states[v]] + pr = pr[states[w]] + pl_transition, pl_unique = rank_reveal(pl, :PE) + pr_transition, pr_unique = rank_reveal(pr, :PE) + en = en[pl_unique, pr_unique] + + set_props!( + new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) + ) + end + new_fg +end + +function compute_factor(fg, src_node, dst_node, beta) + if has_edge(fg, src_node, dst_node) + E_bond = get_prop(fg, src_node, dst_node, :en) + pl, pr = get_prop(fg, src_node, dst_node, :pl), get_prop(fg, src_node, dst_node, :pr) + E_bond = E_bond[pl, pr] + E_neighbor = get_prop(fg, dst_node, :spectrum).energies + E_bond = E_bond .+ reshape(E_neighbor, (1, :)) + factor = exp.(-E_bond * beta) + elseif has_edge(fg, dst_node, src_node) + E_bond = get_prop(fg, dst_node, src_node, :en) + pl, pr = get_prop(fg, dst_node, src_node, :pl), get_prop(fg, dst_node, src_node, :pr) + E_bond = E_bond[pl, pr]' + E_neighbor = get_prop(fg, dst_node, :spectrum).energies + E_bond = E_bond .+ reshape(E_neighbor, (1, :)) + factor = exp.(-E_bond * beta) + end + factor end \ No newline at end of file From 5b875203314e635c00a89d68750b94e5dc0355b2 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Mon, 3 Jul 2023 15:28:21 +0200 Subject: [PATCH 139/218] iterations as a parameter in BP --- src/factor.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index a97a9ce..9079565 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -296,7 +296,7 @@ function get_neighbors(graph::LabelledGraph{S, T}, vertex::Tuple{Any, Any, Any}) end # Works for Pegasus and Zephyr -function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta::Real, num_states::Int) where {S, T} +function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta::Real, num_states::Int, iter::Int) where {S, T} states = Dict() messages = Dict{Tuple{Any, Any}, Array{Any}}() beliefs = Dict{Tuple{Any, Any, Any}, Array{Any}}() @@ -327,7 +327,7 @@ function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta: # Perform message passing until convergence converged = false iteration = 0 - while !converged && iteration < 100 # Set an appropriate number of iterations and convergence threshold + while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold iteration += 1 println("iteration", iteration) old_beliefs = beliefs From 08627256909a92040468c16d16c2ef5d60fee810 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Mon, 3 Jul 2023 15:30:10 +0200 Subject: [PATCH 140/218] remove println --- src/factor.jl | 3 --- 1 file changed, 3 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 9079565..eec04ab 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -329,12 +329,9 @@ function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta: iteration = 0 while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold iteration += 1 - println("iteration", iteration) old_beliefs = beliefs for v in vertices(fg) - println("v", v) for neighbor in get_neighbors(fg, v) - println("neighbor", neighbor) #update messages if has_edge(fg, v, neighbor) messages[(neighbor, (v, neighbor))] = beliefs[neighbor]./messages[(v, neighbor), neighbor] From fba84ade0d860f621488b9a53d2459b7595d91c8 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 7 Jul 2023 11:11:28 +0200 Subject: [PATCH 141/218] clean belief propagation --- src/factor.jl | 47 +++++++++++++++++++++++++++++++---------------- 1 file changed, 31 insertions(+), 16 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index eec04ab..6080867 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -304,20 +304,17 @@ function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta: # Initialize messages with uniform probabilities for v in vertices(fg) ns = length(get_prop(fg, v, :spectrum).states) - belief = ones(ns)/ns + belief = ones(ns)./ns push!(beliefs, v => belief) for neighbor in get_neighbors(fg, v) + message_av = ones(ns)./ns + message_va = ones(ns)./ns + if has_edge(fg, v, neighbor) - pl, pr = get_prop(fg, v, neighbor, :pl), get_prop(fg, v, neighbor, :pr) - message_av = ones(ns)/ns - message_va = ones(ns)/ns push!(messages, (v, (v, neighbor)) => message_va) push!(messages, ((v, neighbor), v) => message_av) elseif has_edge(fg, neighbor, v) - pl, pr = get_prop(fg, neighbor, v, :pl), get_prop(fg, neighbor, v, :pr) - message_av = ones(ns)/ns - message_va = ones(ns)/ns push!(messages, (v, (neighbor, v)) => message_va) push!(messages, ((neighbor, v), v) => message_av) end @@ -332,19 +329,30 @@ function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta: old_beliefs = beliefs for v in vertices(fg) for neighbor in get_neighbors(fg, v) - #update messages + #update messages from vertex to edge if has_edge(fg, v, neighbor) messages[(neighbor, (v, neighbor))] = beliefs[neighbor]./messages[(v, neighbor), neighbor] - messages[((v, neighbor), v)] = compute_factor(fg, v, neighbor, beta) * messages[(neighbor, (v, neighbor))] elseif has_edge(fg, neighbor, v) messages[(neighbor, (neighbor, v))] = beliefs[neighbor]./messages[(neighbor, v), neighbor] + end + end + end + messages = normalize_dict(messages) + for v in vertices(fg) + for neighbor in get_neighbors(fg, v) + #update messages from edge to vertex + if has_edge(fg, v, neighbor) + messages[((v, neighbor), v)] = compute_factor(fg, v, neighbor, beta) * messages[(neighbor, (v, neighbor))] + elseif has_edge(fg, neighbor, v) messages[((neighbor, v), v)] = compute_factor(fg, neighbor, v, beta)' * messages[(neighbor, (neighbor, v))] end end end + messages = normalize_dict(messages) + for v in vertices(fg) E_local = get_prop(fg, v, :spectrum).energies - messages_product = E_local./sum(E_local) + messages_product = exp.(-E_local * beta) for neighbor in get_neighbors(fg, v) #update beliefs if has_edge(fg, v, neighbor) @@ -357,15 +365,15 @@ function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta: # Normalize the beliefs beliefs[v] ./= sum(beliefs[v]) end + # Check convergence if all([all(abs.(old_beliefs[v] .- beliefs[v]) .< 1e-6) for v in keys(beliefs)]) converged = true end end - # Truncate the state space based on the belief probabilities for node in vertices(fg) - indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node]))) + indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node])), rev=true) push!(states, node => indices) end @@ -404,16 +412,23 @@ function compute_factor(fg, src_node, dst_node, beta) E_bond = get_prop(fg, src_node, dst_node, :en) pl, pr = get_prop(fg, src_node, dst_node, :pl), get_prop(fg, src_node, dst_node, :pr) E_bond = E_bond[pl, pr] - E_neighbor = get_prop(fg, dst_node, :spectrum).energies - E_bond = E_bond .+ reshape(E_neighbor, (1, :)) factor = exp.(-E_bond * beta) elseif has_edge(fg, dst_node, src_node) E_bond = get_prop(fg, dst_node, src_node, :en) pl, pr = get_prop(fg, dst_node, src_node, :pl), get_prop(fg, dst_node, src_node, :pr) E_bond = E_bond[pl, pr]' - E_neighbor = get_prop(fg, dst_node, :spectrum).energies - E_bond = E_bond .+ reshape(E_neighbor, (1, :)) factor = exp.(-E_bond * beta) end factor +end + +function normalize_dict(beliefs::Dict) + normalized = Dict() + for k in keys(beliefs) + push!(normalized, k => exp.(beliefs[k])) + end + for k in keys(normalized) + normalized[k] ./= sum(normalized[k]) + end + normalized end \ No newline at end of file From 9da752dd36b1da1f33c5423a2c17b16f55a7c129 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 7 Jul 2023 11:11:46 +0200 Subject: [PATCH 142/218] clean up BP --- src/factor.jl | 13 ------------- 1 file changed, 13 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 6080867..cd54875 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -337,7 +337,6 @@ function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta: end end end - messages = normalize_dict(messages) for v in vertices(fg) for neighbor in get_neighbors(fg, v) #update messages from edge to vertex @@ -348,7 +347,6 @@ function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta: end end end - messages = normalize_dict(messages) for v in vertices(fg) E_local = get_prop(fg, v, :spectrum).energies @@ -421,14 +419,3 @@ function compute_factor(fg, src_node, dst_node, beta) end factor end - -function normalize_dict(beliefs::Dict) - normalized = Dict() - for k in keys(beliefs) - push!(normalized, k => exp.(beliefs[k])) - end - for k in keys(normalized) - normalized[k] ./= sum(normalized[k]) - end - normalized -end \ No newline at end of file From ffcb14c943e61a62e17a1f3934b55544e849169a Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 7 Jul 2023 12:12:31 +0200 Subject: [PATCH 143/218] belief propagation --- src/factor.jl | 151 ++++++++++++++++++++------------------------- test/bp_pegasus.jl | 63 +++++++++++++++++++ 2 files changed, 129 insertions(+), 85 deletions(-) create mode 100644 test/bp_pegasus.jl diff --git a/src/factor.jl b/src/factor.jl index cd54875..3bf719b 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -9,7 +9,8 @@ export # truncate_factor_graph_2site, truncate_factor_graph_2site_precise, truncate_factor_graph_1site_meanfield, - truncate_factor_graph_belief_propagation + truncate_factor_graph_belief_propagation, + belief_propagation """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ @@ -282,7 +283,7 @@ function select_numstate_best(E, sx, num_states) end end -function get_neighbors(graph::LabelledGraph{S, T}, vertex::Tuple{Any, Any, Any}) where {S, T} +function get_neighbors(graph::LabelledGraph{S, T}, vertex::NTuple) where {S, T} neighbors = [] for edge in edges(graph) src_node, dst_node = src(edge), dst(edge) @@ -296,28 +297,58 @@ function get_neighbors(graph::LabelledGraph{S, T}, vertex::Tuple{Any, Any, Any}) end # Works for Pegasus and Zephyr -function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta::Real, num_states::Int, iter::Int) where {S, T} +function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta::Real, num_states::Int; tol=1e-6, iter=1) where {S, T} states = Dict() - messages = Dict{Tuple{Any, Any}, Array{Any}}() - beliefs = Dict{Tuple{Any, Any, Any}, Array{Any}}() + beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) + + # Truncate the state space based on the belief probabilities + for node in vertices(fg) + indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node])), rev=true) + push!(states, node => indices) + end + + # Create a new factor graph with truncated state space + new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) + + for v ∈ vertices(new_fg) + cl = get_prop(fg, v, :cluster) + sp = get_prop(fg, v, :spectrum) + sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) + set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) + end + + for e ∈ edges(fg) + v, w = src(e), dst(e) + add_edge!(new_fg, v, w) + outer_edges = get_prop(fg, v, w, :outer_edges) + pl = get_prop(fg, v, w, :pl) + pr = get_prop(fg, v, w, :pr) + en = get_prop(fg, v, w, :en) + pl = pl[states[v]] + pr = pr[states[w]] + pl_transition, pl_unique = rank_reveal(pl, :PE) + pr_transition, pr_unique = rank_reveal(pr, :PE) + en = en[pl_unique, pr_unique] + + set_props!( + new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) + ) + end + new_fg +end + +function belief_propagation(fg, beta; tol=1e-6, iter=1) + messages_va = Dict() + messages_av = Dict() + beliefs = Dict() # Initialize messages with uniform probabilities for v in vertices(fg) ns = length(get_prop(fg, v, :spectrum).states) - belief = ones(ns)./ns - push!(beliefs, v => belief) - + push!(beliefs, v => ones(ns)./ns) for neighbor in get_neighbors(fg, v) - message_av = ones(ns)./ns - message_va = ones(ns)./ns - - if has_edge(fg, v, neighbor) - push!(messages, (v, (v, neighbor)) => message_va) - push!(messages, ((v, neighbor), v) => message_av) - elseif has_edge(fg, neighbor, v) - push!(messages, (v, (neighbor, v)) => message_va) - push!(messages, ((neighbor, v), v) => message_av) - end + push!(messages_va, (v, neighbor) => ones(ns)./ns) + push!(messages_av, (neighbor, v) => ones(ns)./ns) end end @@ -326,96 +357,46 @@ function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta: iteration = 0 while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold iteration += 1 - old_beliefs = beliefs + println(iteration) + old_beliefs = deepcopy(beliefs) for v in vertices(fg) for neighbor in get_neighbors(fg, v) #update messages from vertex to edge - if has_edge(fg, v, neighbor) - messages[(neighbor, (v, neighbor))] = beliefs[neighbor]./messages[(v, neighbor), neighbor] - elseif has_edge(fg, neighbor, v) - messages[(neighbor, (neighbor, v))] = beliefs[neighbor]./messages[(neighbor, v), neighbor] - end + messages_va[v, neighbor] = beliefs[v]./messages_av[neighbor, v] + messages_va[v, neighbor] ./= sum(messages_va[v, neighbor]) end end for v in vertices(fg) for neighbor in get_neighbors(fg, v) #update messages from edge to vertex if has_edge(fg, v, neighbor) - messages[((v, neighbor), v)] = compute_factor(fg, v, neighbor, beta) * messages[(neighbor, (v, neighbor))] + E_bond = get_prop(fg, v, neighbor, :en) + pl, pr = get_prop(fg, v, neighbor, :pl), get_prop(fg, v, neighbor, :pr) + E_bond = E_bond[pl, pr] elseif has_edge(fg, neighbor, v) - messages[((neighbor, v), v)] = compute_factor(fg, neighbor, v, beta)' * messages[(neighbor, (neighbor, v))] + E_bond = get_prop(fg, neighbor, v, :en) + pl, pr = get_prop(fg, neighbor, v, :pl), get_prop(fg, neighbor, v, :pr) + E_bond = E_bond[pl, pr]' end + messages_av[neighbor, v] = exp.(-beta * E_bond) * messages_va[neighbor, v] + messages_av[neighbor, v] ./= sum(messages_av[neighbor, v]) end end for v in vertices(fg) E_local = get_prop(fg, v, :spectrum).energies - messages_product = exp.(-E_local * beta) + beliefs[v] = exp.(-E_local * beta) for neighbor in get_neighbors(fg, v) #update beliefs - if has_edge(fg, v, neighbor) - messages_product .*= messages[((v, neighbor), v)] - elseif has_edge(fg, neighbor, v) - messages_product .*= messages[((neighbor, v), v)] - end + beliefs[v] .*= messages_av[neighbor, v] end - beliefs[v] = messages_product # Normalize the beliefs beliefs[v] ./= sum(beliefs[v]) end # Check convergence - if all([all(abs.(old_beliefs[v] .- beliefs[v]) .< 1e-6) for v in keys(beliefs)]) - converged = true - end - end - # Truncate the state space based on the belief probabilities - for node in vertices(fg) - indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node])), rev=true) - push!(states, node => indices) + converged = all([all(abs.(old_beliefs[v] .- beliefs[v]) .< tol) for v in keys(beliefs)]) end - # Create a new factor graph with truncated state space - new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) - - for v ∈ vertices(new_fg) - cl = get_prop(fg, v, :cluster) - sp = get_prop(fg, v, :spectrum) - sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) - set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) - end - - for e ∈ edges(fg) - v, w = src(e), dst(e) - add_edge!(new_fg, v, w) - outer_edges = get_prop(fg, v, w, :outer_edges) - pl = get_prop(fg, v, w, :pl) - pr = get_prop(fg, v, w, :pr) - en = get_prop(fg, v, w, :en) - pl = pl[states[v]] - pr = pr[states[w]] - pl_transition, pl_unique = rank_reveal(pl, :PE) - pr_transition, pr_unique = rank_reveal(pr, :PE) - en = en[pl_unique, pr_unique] - - set_props!( - new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) - ) - end - new_fg -end - -function compute_factor(fg, src_node, dst_node, beta) - if has_edge(fg, src_node, dst_node) - E_bond = get_prop(fg, src_node, dst_node, :en) - pl, pr = get_prop(fg, src_node, dst_node, :pl), get_prop(fg, src_node, dst_node, :pr) - E_bond = E_bond[pl, pr] - factor = exp.(-E_bond * beta) - elseif has_edge(fg, dst_node, src_node) - E_bond = get_prop(fg, dst_node, src_node, :en) - pl, pr = get_prop(fg, dst_node, src_node, :pl), get_prop(fg, dst_node, src_node, :pr) - E_bond = E_bond[pl, pr]' - factor = exp.(-E_bond * beta) - end - factor -end + beliefs +end \ No newline at end of file diff --git a/test/bp_pegasus.jl b/test/bp_pegasus.jl new file mode 100644 index 0000000..9c89e94 --- /dev/null +++ b/test/bp_pegasus.jl @@ -0,0 +1,63 @@ +""" +Instance below looks like this: + +1 -- 2 + + + +""" +function create_larger_example_factor_graph_tree() + instance = Dict( + (1, 1) => 0.5, + (2, 2) => 0.25, + # (3, 3) => 0.3, + # (4, 4) => 0.1, + # (5, 5) => 0.1, + # (6, 6) => -2.0, + (1, 2) => -1.0, + # (1, 3) => 1.0 + # (2, 4) => 1.0, + # (3, 4) => 1.0, + # (1, 5) => 0.5, + # (2, 5) => 0.5, + # (2, 6) => 0.5, + # (5, 6) => -0.3, + ) + + ig = ising_graph(instance) + + assignment_rule = Dict( + 1 => (1, 1, 1), + 2 => (1, 2, 1), + # 3 => (2, 1, 1) + # 4 => (1, 2, 2), + # 5 => (2, 1, 1), + # 6 => (2, 1, 2), + ) + + fg = factor_graph( + ig, + Dict{NTuple{3, Int}, Int}(), + spectrum = full_spectrum, + cluster_assignment_rule = assignment_rule, + ) + + ig, fg +end + +function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors + ver = vertices(factor_graph) + rank = cluster_size.(Ref(factor_graph), ver) + states = [Dict(ver .=> σ) for σ ∈ Iterators.product([1:r for r ∈ rank]...)] + energies = SpinGlassNetworks.energy.(Ref(factor_graph), states) + prob = exp.(-beta .* energies) + prob ./= sum(prob) + sum(prob[findall([all(s[k] == v for (k, v) ∈ target_state) for s ∈ states])]) +end + +ig, fg = create_larger_example_factor_graph_tree() +beta = 1 +beliefs = belief_propagation(fg, beta; iter=100) +println(beliefs) + +println(exact_cond_prob(fg, beta, Dict((1, 1, 1) => 1))) From 58d02fb7a9b1a59889363d65ccc2640900d796c1 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 7 Jul 2023 12:30:45 +0200 Subject: [PATCH 144/218] remove println --- src/factor.jl | 1 - 1 file changed, 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 3bf719b..ae68661 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -357,7 +357,6 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) iteration = 0 while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold iteration += 1 - println(iteration) old_beliefs = deepcopy(beliefs) for v in vertices(fg) for neighbor in get_neighbors(fg, v) From 7a0d5d32b5cf82217d89d2c230d35e526d1024d7 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 7 Jul 2023 14:15:15 +0200 Subject: [PATCH 145/218] BP tests --- src/factor.jl | 15 +++- test/bp_pegasus.jl | 177 ++++++++++++++++++++++++++++++++++++++------- test/runtests.jl | 7 +- 3 files changed, 166 insertions(+), 33 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index ae68661..cd7ccff 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -10,7 +10,8 @@ export truncate_factor_graph_2site_precise, truncate_factor_graph_1site_meanfield, truncate_factor_graph_belief_propagation, - belief_propagation + belief_propagation, + exact_cond_prob """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ @@ -398,4 +399,14 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) end beliefs -end \ No newline at end of file +end + +function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors + ver = vertices(factor_graph) + rank = cluster_size.(Ref(factor_graph), ver) + states = [Dict(ver .=> σ) for σ ∈ Iterators.product([1:r for r ∈ rank]...)] + energies = SpinGlassNetworks.energy.(Ref(factor_graph), states) + prob = exp.(-beta .* energies) + prob ./= sum(prob) + sum(prob[findall([all(s[k] == v for (k, v) ∈ target_state) for s ∈ states])]) + end \ No newline at end of file diff --git a/test/bp_pegasus.jl b/test/bp_pegasus.jl index 9c89e94..e0c3c77 100644 --- a/test/bp_pegasus.jl +++ b/test/bp_pegasus.jl @@ -2,26 +2,68 @@ Instance below looks like this: 1 -- 2 +| +3 -- 4 +""" +function create_larger_example_factor_graph_tree_basic() + instance = Dict( + (1, 1) => 0.5, + (2, 2) => 0.25, + (3, 3) => 0.3, + (4, 4) => 0.1, + (1, 2) => -1.0, + (1, 3) => 1.0, + (3, 4) => 1.0 + ) + + ig = ising_graph(instance) + + assignment_rule = Dict( + 1 => (1, 1, 1), + 2 => (1, 2, 1), + 3 => (2, 1, 1), + 4 => (2, 2, 2) + ) + fg = factor_graph( + ig, + Dict{NTuple{3, Int}, Int}(), + spectrum = full_spectrum, + cluster_assignment_rule = assignment_rule, + ) + + ig, fg +end + +""" +Instance below looks like this: +1 -- 2 -- 3 +| +4 -- 5 -- 6 +| +7 -- 8 -- 9 """ function create_larger_example_factor_graph_tree() instance = Dict( (1, 1) => 0.5, (2, 2) => 0.25, - # (3, 3) => 0.3, - # (4, 4) => 0.1, - # (5, 5) => 0.1, - # (6, 6) => -2.0, + (3, 3) => 0.3, + (4, 4) => 0.1, + (5, 5) => -0.1, + (6, 6) => 0.1, + (7, 7) => 0.0, + (8, 8) => 0.1, + (9, 9) => 0.01, (1, 2) => -1.0, - # (1, 3) => 1.0 - # (2, 4) => 1.0, - # (3, 4) => 1.0, - # (1, 5) => 0.5, - # (2, 5) => 0.5, - # (2, 6) => 0.5, - # (5, 6) => -0.3, + (2, 3) => 1.0, + (1, 4) => 1.0, + (4, 5) => 1.0, + (5, 6) => 1.0, + (4, 7) => 1.0, + (7, 8) => 1.0, + (8, 9) => 1.0 ) ig = ising_graph(instance) @@ -29,10 +71,13 @@ function create_larger_example_factor_graph_tree() assignment_rule = Dict( 1 => (1, 1, 1), 2 => (1, 2, 1), - # 3 => (2, 1, 1) - # 4 => (1, 2, 2), - # 5 => (2, 1, 1), - # 6 => (2, 1, 2), + 3 => (1, 3, 1), + 4 => (2, 1, 1), + 5 => (2, 2, 1), + 6 => (2, 3, 1), + 7 => (3, 1, 1), + 8 => (3, 2, 1), + 9 => (3, 3, 1) ) fg = factor_graph( @@ -45,19 +90,95 @@ function create_larger_example_factor_graph_tree() ig, fg end -function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors - ver = vertices(factor_graph) - rank = cluster_size.(Ref(factor_graph), ver) - states = [Dict(ver .=> σ) for σ ∈ Iterators.product([1:r for r ∈ rank]...)] - energies = SpinGlassNetworks.energy.(Ref(factor_graph), states) - prob = exp.(-beta .* energies) - prob ./= sum(prob) - sum(prob[findall([all(s[k] == v for (k, v) ∈ target_state) for s ∈ states])]) +""" +Instance below looks like this: + +1 -- 2 -- 3 +| | +4 5 + +""" +function create_larger_example_factor_graph_tree_pathological() + instance = Dict( + (1, 1) => 0.5, + (2, 2) => 0.25, + (3, 3) => 0.3, + (4, 4) => 0.1, + (5, 5) => -0.1, + (6, 6) => 0.1, + (7, 7) => 0.0, + (8, 8) => 0.1, + (1, 2) => -1.0, + (1, 3) => 1.0, + (3, 4) => 1.0, + (3, 5) => 1.0, + (5, 6) => 1.0, + (2, 7) => 0.5, + (3, 7) => 1.0, + (5, 8) => 1.0, + + ) + + ig = ising_graph(instance) + + assignment_rule = Dict( + 1 => (1, 1), + 2 => (1, 1), + 3 => (1, 1), + 4 => (1, 2), + 5 => (1, 2), + 6 => (1, 3), + 7 => (2, 1), + 8 => (2, 2) + ) + + fg = factor_graph( + ig, + Dict{NTuple{2, Int}, Int}(), + spectrum = full_spectrum, + cluster_assignment_rule = assignment_rule, + ) + + ig, fg end -ig, fg = create_larger_example_factor_graph_tree() -beta = 1 -beliefs = belief_propagation(fg, beta; iter=100) -println(beliefs) -println(exact_cond_prob(fg, beta, Dict((1, 1, 1) => 1))) +@testset "Belief propagation basic" begin + ig, fg = create_larger_example_factor_graph_tree_basic() + beta = 1 + iter = 100 + beliefs = belief_propagation(fg, beta; iter=iter) + exact_marginal = Dict() + for k in keys(beliefs) + push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + end + for v in keys(beliefs) + @test beliefs[v] ≈ exact_marginal[v] + end +end +@testset "Belief propagation " begin + ig, fg = create_larger_example_factor_graph_tree() + beta = 1 + iter = 100 + beliefs = belief_propagation(fg, beta; iter=iter) + exact_marginal = Dict() + for k in keys(beliefs) + push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + end + for v in keys(beliefs) + @test beliefs[v] ≈ exact_marginal[v] + end +end +@testset "Belief propagation pathological" begin + ig, fg = create_larger_example_factor_graph_tree_pathological() + beta = 1 + iter = 100 + beliefs = belief_propagation(fg, beta; iter=iter) + exact_marginal = Dict() + for k in keys(beliefs) + push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + end + for v in keys(beliefs) + @test beliefs[v] ≈ exact_marginal[v] + end +end \ No newline at end of file diff --git a/test/runtests.jl b/test/runtests.jl index a31f9f2..a4bc0b0 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -27,9 +27,10 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) end my_tests = [ - "ising.jl", - "factor.jl", - "utils.jl", + # "ising.jl", + # "factor.jl", + # "utils.jl", + "bp_pegasus.jl" ] for my_test ∈ my_tests From 6093ff705d5f4f610a0e095231fac511bea28cda Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 7 Jul 2023 16:29:28 +0200 Subject: [PATCH 146/218] truncate_factor_graph_2site_BP --- src/factor.jl | 241 +++++++++++++++++++++------------------------ test/bp_pegasus.jl | 80 +++++++++++++++ 2 files changed, 195 insertions(+), 126 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index cd7ccff..237ded4 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -6,12 +6,11 @@ export decode_factor_graph_state, energy, cluster_size, - # truncate_factor_graph_2site, - truncate_factor_graph_2site_precise, - truncate_factor_graph_1site_meanfield, - truncate_factor_graph_belief_propagation, + truncate_factor_graph_2site_energy, + truncate_factor_graph_1site_BP, belief_propagation, - exact_cond_prob + exact_cond_prob, + beliefs_2site """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ @@ -143,132 +142,33 @@ function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} length(get_prop(factor_graph, vertex, :spectrum).energies) end -function truncate_factor_graph_1site_meanfield(fg::LabelledGraph{S, T}, beta::Real, num_states::Int) where {S, T} - states = Dict() - for node in vertices(fg) - E = copy(get_prop(fg, node, :spectrum).energies) - for n in vertices(fg) - if has_edge(fg, node, n) - E_bond = get_prop(fg, node, n, :en) - pl, pr = get_prop(fg, node, n, :pl), get_prop(fg, node, n, :pr) - E_bond = E_bond[pl, pr] - E_neighbor = get_prop(fg, n, :spectrum).energies - E_bond = E_bond .+ reshape(E_neighbor, (1, :)) - E .+= log.(sum(exp.(-E_bond * beta), dims=2))./(-beta) - elseif has_edge(fg, n, node) - E_bond = get_prop(fg, n, node, :en) - pl, pr = get_prop(fg, n, node, :pl), get_prop(fg, n, node, :pr) - E_bond = E_bond[pl, pr]' - E_neighbor = get_prop(fg, n, :spectrum).energies - E_bond = E_bond .+ reshape(E_neighbor, (1, :)) - E .+= log.(sum(exp.(-E_bond * beta), dims=2))./(-beta) - end - end - push!(states, node => partialsortperm(E, 1:min(num_states, length(E)))) - end - - - new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) - - for v ∈ vertices(new_fg) - cl = get_prop(fg, v, :cluster) - sp = get_prop(fg, v, :spectrum) - sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) - set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) - end - - for e ∈ edges(fg) - v, w = src(e), dst(e) - add_edge!(new_fg, v, w) - outer_edges = get_prop(fg, v, w, :outer_edges) - pl = get_prop(fg, v, w, :pl) - pr = get_prop(fg, v, w, :pr) - en = get_prop(fg, v, w, :en) - pl = pl[states[v]] - pr = pr[states[w]] - pl_transition, pl_unique = rank_reveal(pl, :PE) - pr_transition, pr_unique = rank_reveal(pr, :PE) - en = en[pl_unique, pr_unique] - set_props!( - new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) - ) - end - new_fg -end - -function truncate_factor_graph_2site_precise(fg::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 +function truncate_factor_graph_2site_energy(fg::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 states = Dict() for node in vertices(fg) if node in keys(states) continue end i, j, _ = node E1 = copy(get_prop(fg, (i, j, 1), :spectrum).energies) E2 = copy(get_prop(fg, (i, j, 2), :spectrum).energies) - if has_edge(fg, (i, j, 1), (i, j, 2)) - en12 = copy(get_prop(fg, (i, j, 1), (i, j, 2), :en)) - pl = copy(get_prop(fg, (i, j, 1), (i, j, 2), :pl)) - pr = copy(get_prop(fg, (i, j, 1), (i, j, 2), :pr)) - int_eng = en12[pl, pr] - elseif has_edge(fg, (i, j, 2), (i, j, 1)) - en21 = copy(get_prop(fg, (i, j, 2), (i, j, 1), :en)) - pl = copy(get_prop(fg, (i, j, 2), (i, j, 1), :pl)) - pr = copy(get_prop(fg, (i, j, 2), (i, j, 1), :pr)) - int_eng = en21[pl, pr]' - else - int_eng = zeros(1, 1) - end - E = int_eng .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) + E = -1 .* energy_2site(fg, i, j) .- reshape(E1, :, 1) .- reshape(E2, 1, :) sx, sy = size(E) E = reshape(E, sx * sy) ind1, ind2 = select_numstate_best(E, sx, num_states) push!(states, (i, j, 1) => ind1) push!(states, (i, j, 2) => ind2) end - - new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) - - # sp = empty_spectrum(num_states) - for v ∈ vertices(new_fg) - cl = get_prop(fg, v, :cluster) - sp = get_prop(fg, v, :spectrum) - if sp.states == Vector{Int64}[] - sp = Spectrum(sp.energies[states[v]], []) - else - sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) - end - set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) - end - - for e ∈ edges(fg) - v, w = src(e), dst(e) - add_edge!(new_fg, v, w) - outer_edges = get_prop(fg, v, w, :outer_edges) - pl = get_prop(fg, v, w, :pl) - pr = get_prop(fg, v, w, :pr) - en = get_prop(fg, v, w, :en) - pl = pl[states[v]] - pr = pr[states[w]] - pl_transition, pl_unique = rank_reveal(pl, :PE) - pr_transition, pr_unique = rank_reveal(pr, :PE) - en = en[pl_unique, pr_unique] - - set_props!( - new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) - ) - end - - new_fg + truncate_factor_graph(fg, states) end -# truncate based on energy in two nods of factor graph; resulting states are a product of states in two nodes, so we have to fine-tune to end up with expected number of states +# truncate based on energy in two nodes of factor graph; resulting states are a product of states in two nodes, so we have to fine-tune to end up with expected number of states function select_numstate_best(E, sx, num_states) low, high = 1, min(num_states, length(E)) while true guess = div(low + high, 2) - ind = partialsortperm(E, 1:guess) + ind = partialsortperm(E, 1:guess, rev=true) ind1 = mod.(ind .- 1, sx) .+ 1 ind2 = div.(ind .- 1, sx) .+ 1 ind1 = sort([Set(ind1)...]) @@ -298,17 +198,8 @@ function get_neighbors(graph::LabelledGraph{S, T}, vertex::NTuple) where {S, T} end # Works for Pegasus and Zephyr -function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta::Real, num_states::Int; tol=1e-6, iter=1) where {S, T} - states = Dict() - beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) +function truncate_factor_graph(fg::LabelledGraph{S, T}, states::Dict) where {S, T} - # Truncate the state space based on the belief probabilities - for node in vertices(fg) - indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node])), rev=true) - push!(states, node => indices) - end - - # Create a new factor graph with truncated state space new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) for v ∈ vertices(new_fg) @@ -338,7 +229,102 @@ function truncate_factor_graph_belief_propagation(fg::LabelledGraph{S, T}, beta: new_fg end -function belief_propagation(fg, beta; tol=1e-6, iter=1) +function truncate_factor_graph_1site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} + states = Dict() + beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) + for node in vertices(fg) + indices = partialsortperm(weights[node], 1:min(num_states, length(weights[node])), rev=true) + push!(states, node => indices) + end + truncate_factor_graph(fg, states) +end + +function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} + states = Dict() + beliefs, messages_av = belief_propagation(fg, beta; tol=tol, iter=iter, output_message=true) + + for node in vertices(fg) + if node in keys(states) continue end + i, j, _ = node + temp = beliefs_2site(fg, i, j, messages_av, beta) + sx, sy = size(temp) + temp = reshape(temp, sx * sy) + ind1, ind2 = select_numstate_best(temp, sx, num_states) + push!(states, (i, j, 1) => ind1) + push!(states, (i, j, 2) => ind2) + end + + truncate_factor_graph(fg, states) +end + +function beliefs_2site(fg::LabelledGraph{S, T}, i::Int, j::Int, messages_av::Dict, beta::Real) where {S, T} + temp = energy_2site(fg, i, j) + temp = exp.(-beta*temp) + if ((i, j, 1), (i, j, 2)) in keys(messages_av) + temp = temp .* reshape(messages_av[(i, j, 1), (i, j, 2)], :, 1) + temp = temp .*reshape(messages_av[(i, j, 2), (i, j, 1)], 1, :) + end + temp ./= sum(temp) +end + +function energy_2site(fg::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} + if has_edge(fg, (i, j, 1), (i, j, 2)) + en12 = copy(get_prop(fg, (i, j, 1), (i, j, 2), :en)) + pl = copy(get_prop(fg, (i, j, 1), (i, j, 2), :pl)) + pr = copy(get_prop(fg, (i, j, 1), (i, j, 2), :pr)) + int_eng = en12[pl, pr] + elseif has_edge(fg, (i, j, 2), (i, j, 1)) + en21 = copy(get_prop(fg, (i, j, 2), (i, j, 1), :en)) + pl = copy(get_prop(fg, (i, j, 2), (i, j, 1), :pl)) + pr = copy(get_prop(fg, (i, j, 2), (i, j, 1), :pr)) + int_eng = en21[pl, pr]' + else + int_eng = zeros(1, 1) + end + int_eng +end +# Works for Pegasus and Zephyr +# function truncate_factor_graph_1site(fg::LabelledGraph{S, T}, beta::Real, num_states::Int; tol=1e-6, iter=1) where {S, T} +# states = Dict() +# beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) + +# # Truncate the state space based on the belief probabilities +# for node in vertices(fg) +# indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node])), rev=true) +# push!(states, node => indices) +# end + +# # Create a new factor graph with truncated state space +# new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) + +# for v ∈ vertices(new_fg) +# cl = get_prop(fg, v, :cluster) +# sp = get_prop(fg, v, :spectrum) +# sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) +# set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) +# end + +# for e ∈ edges(fg) +# v, w = src(e), dst(e) +# add_edge!(new_fg, v, w) +# outer_edges = get_prop(fg, v, w, :outer_edges) +# pl = get_prop(fg, v, w, :pl) +# pr = get_prop(fg, v, w, :pr) +# en = get_prop(fg, v, w, :en) +# pl = pl[states[v]] +# pr = pr[states[w]] +# pl_transition, pl_unique = rank_reveal(pl, :PE) +# pr_transition, pr_unique = rank_reveal(pr, :PE) +# en = en[pl_unique, pr_unique] + +# set_props!( +# new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) +# ) +# end +# new_fg +# end + +function belief_propagation(fg, beta; tol=1e-6, iter=1, output_message=false) messages_va = Dict() messages_av = Dict() beliefs = Dict() @@ -372,13 +358,16 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) if has_edge(fg, v, neighbor) E_bond = get_prop(fg, v, neighbor, :en) pl, pr = get_prop(fg, v, neighbor, :pl), get_prop(fg, v, neighbor, :pr) - E_bond = E_bond[pl, pr] elseif has_edge(fg, neighbor, v) - E_bond = get_prop(fg, neighbor, v, :en) - pl, pr = get_prop(fg, neighbor, v, :pl), get_prop(fg, neighbor, v, :pr) - E_bond = E_bond[pl, pr]' + E_bond = get_prop(fg, neighbor, v, :en)' + pl, pr = get_prop(fg, neighbor, v, :pr), get_prop(fg, neighbor, v, :pl) + end + temp = zeros(maximum(pr)) + for (i, r) in enumerate(pr) + temp[r] += messages_va[neighbor, v][i] end - messages_av[neighbor, v] = exp.(-beta * E_bond) * messages_va[neighbor, v] + temp = exp.(-beta * E_bond) * temp + messages_av[neighbor, v] = temp[pl] messages_av[neighbor, v] ./= sum(messages_av[neighbor, v]) end end @@ -398,7 +387,7 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) converged = all([all(abs.(old_beliefs[v] .- beliefs[v]) .< tol) for v in keys(beliefs)]) end - beliefs + output_message ? (beliefs, messages_av) : beliefs end function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors diff --git a/test/bp_pegasus.jl b/test/bp_pegasus.jl index e0c3c77..207b593 100644 --- a/test/bp_pegasus.jl +++ b/test/bp_pegasus.jl @@ -142,6 +142,58 @@ function create_larger_example_factor_graph_tree_pathological() ig, fg end +""" +Instance below looks like this: + +1 -- 2 +| +3 -- 4 + +""" +function create_larger_example_factor_graph_tree_2site() + instance = Dict( + (1, 1) => 0.5, + (2, 2) => 0.25, + (3, 3) => 0.3, + (4, 4) => 0.1, + (5, 5) => 0.1, + (6, 6) => 0.1, + (7, 7) => 0.1, + (8, 8) => 0.1, + (1, 2) => -0.00001, + (1, 3) => 1.0, + (3, 4) => 1.0, + (2, 5) => 1.0, + (3, 4) => 1.0, + (6, 7) => 1.0, + (6, 8) => 1.0, + (6, 2) => 1.0 + ) + + ig = ising_graph(instance) + + assignment_rule = Dict( + 1 => (1, 1, 1), + 2 => (1, 1, 2), + 3 => (1, 2, 1), + 4 => (1, 2, 2), + 5 => (2, 1, 1), + 6 => (2, 1, 2), + 7 => (2, 2, 1), + 8 => (2, 2, 2) + ) + + fg = factor_graph( + ig, + Dict{NTuple{3, Int}, Int}(), + spectrum = full_spectrum, + cluster_assignment_rule = assignment_rule, + ) + + ig, fg +end + + @testset "Belief propagation basic" begin ig, fg = create_larger_example_factor_graph_tree_basic() @@ -181,4 +233,32 @@ end for v in keys(beliefs) @test beliefs[v] ≈ exact_marginal[v] end +end + +@testset "Belief propagation 2site" begin + ig, fg = create_larger_example_factor_graph_tree_2site() + beta = 1 + tol = 1e-12 + iter = 100 + beliefs, messages_av = belief_propagation(fg, beta; iter=iter, tol=tol, output_message=true) + exact_marginal = Dict() + for k in keys(beliefs) + push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + end + for v in keys(beliefs) + @test beliefs[v] ≈ exact_marginal[v] + end + + for v in vertices(fg) + println("v ", v) + i, j, _ = v + n1, n2 = length(beliefs[(i, j, 1)]), length(beliefs[(i, j, 2)]) + exact = [exact_cond_prob(fg, beta, Dict((i, j, 1) => k1, (i, j, 2) => k2)) for k1 in 1:n1, k2 in 1:n2] + println("exact ", exact) + belief = beliefs_2site(fg, i, j, messages_av, beta) + println("belief ", belief) + + # @test beliefs_2site(fg, i, j, messages_av, beta) ≈ exact + end + end \ No newline at end of file From bc31b216ced8fe6b4ad11fe3df6ba597023bcb1d Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Mon, 17 Jul 2023 12:59:15 +0200 Subject: [PATCH 147/218] fix the bug in BP --- src/factor.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index 237ded4..6f234c4 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -233,7 +233,7 @@ function truncate_factor_graph_1site_BP(fg::LabelledGraph{S, T}, num_states::Int states = Dict() beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) for node in vertices(fg) - indices = partialsortperm(weights[node], 1:min(num_states, length(weights[node])), rev=true) + indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node])), rev=true) push!(states, node => indices) end truncate_factor_graph(fg, states) From 2a66ff71af0b0fde5c0bf1d725fa12cd0ab56bdb Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Tue, 18 Jul 2023 14:05:39 +0200 Subject: [PATCH 148/218] new BP --- src/factor.jl | 90 +++++++++++++++++++++++++++++++++++++++++++--- test/bp_pegasus.jl | 65 ++++++++++++++++----------------- 2 files changed, 118 insertions(+), 37 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 6f234c4..828aba9 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -9,6 +9,7 @@ export truncate_factor_graph_2site_energy, truncate_factor_graph_1site_BP, belief_propagation, + belief_propagation_old, exact_cond_prob, beliefs_2site """ @@ -150,7 +151,7 @@ function truncate_factor_graph_2site_energy(fg::LabelledGraph{S, T}, num_states: i, j, _ = node E1 = copy(get_prop(fg, (i, j, 1), :spectrum).energies) E2 = copy(get_prop(fg, (i, j, 2), :spectrum).energies) - E = -1 .* energy_2site(fg, i, j) .- reshape(E1, :, 1) .- reshape(E2, 1, :) + E = energy_2site(fg, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) sx, sy = size(E) E = reshape(E, sx * sy) ind1, ind2 = select_numstate_best(E, sx, num_states) @@ -168,7 +169,7 @@ function select_numstate_best(E, sx, num_states) while true guess = div(low + high, 2) - ind = partialsortperm(E, 1:guess, rev=true) + ind = partialsortperm(E, 1:guess) ind1 = mod.(ind .- 1, sx) .+ 1 ind2 = div.(ind .- 1, sx) .+ 1 ind1 = sort([Set(ind1)...]) @@ -233,7 +234,7 @@ function truncate_factor_graph_1site_BP(fg::LabelledGraph{S, T}, num_states::Int states = Dict() beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) for node in vertices(fg) - indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node])), rev=true) + indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node]))) push!(states, node => indices) end truncate_factor_graph(fg, states) @@ -283,6 +284,7 @@ function energy_2site(fg::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} end int_eng end + # Works for Pegasus and Zephyr # function truncate_factor_graph_1site(fg::LabelledGraph{S, T}, beta::Real, num_states::Int; tol=1e-6, iter=1) where {S, T} # states = Dict() @@ -324,7 +326,8 @@ end # new_fg # end -function belief_propagation(fg, beta; tol=1e-6, iter=1, output_message=false) + +function belief_propagation_old(fg, beta; tol=1e-6, iter=1, output_message=false) messages_va = Dict() messages_av = Dict() beliefs = Dict() @@ -398,4 +401,81 @@ function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state:: prob = exp.(-beta .* energies) prob ./= sum(prob) sum(prob[findall([all(s[k] == v for (k, v) ∈ target_state) for s ∈ states])]) - end \ No newline at end of file + end + + function belief_propagation(fg, beta; tol=1e-6, iter=1, output_message=false) + messages_va = Dict() + messages_av = Dict() + beliefs = Dict() + + # Initialize messages with uniform probabilities + for v in vertices(fg) + ns = length(get_prop(fg, v, :spectrum).states) + push!(beliefs, v => ones(ns)./ns) + for neighbor in get_neighbors(fg, v) + pr = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :pr) : get_prop(fg, neighbor, v, :pl) + pl = has_edge(fg, neighbor, v) ? get_prop(fg, neighbor, v, :pr) : get_prop(fg, v, neighbor, :pl) + temp = zeros(maximum(pr)) + for (i, r) in enumerate(pr) + temp[r] += 1 + end + push!(messages_va, (v, neighbor) => temp ./ sum(temp)) + push!(messages_av, (neighbor, v) => ones(maximum(pl))) + end + end + + # Perform message passing until convergence + converged = false + iteration = 0 + while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold + iteration += 1 + old_beliefs = deepcopy(beliefs) + for v in vertices(fg) + for neighbor in get_neighbors(fg, v) + #update messages from vertex to edge + E_local = get_prop(fg, v, :spectrum).energies + E_local = E_local .- minimum(E_local) + messages_va[v, neighbor] = exp.(-E_local * beta) + for n in get_neighbors(fg, v) + if n != neighbor + pl = has_edge(fg, n, v) ? get_prop(fg, n, v, :pr) : get_prop(fg, v, n, :pl) + messages_va[v, neighbor] .*= messages_av[n, v][pl] + end + end + messages_va[v, neighbor] ./= sum(messages_va[v, neighbor]) + pr = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :pl) : get_prop(fg, neighbor, v, :pr) + temp = zeros(maximum(pr)) + for (i, r) in enumerate(pr) + temp[r] += messages_va[v, neighbor][i] + end + messages_va[v, neighbor] = temp + end + end + for v in vertices(fg) + for neighbor in get_neighbors(fg, v) + #update messages from edge to vertex + E_bond = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :en) : get_prop(fg, neighbor, v, :en)' + E_bond = E_bond .- minimum(E_bond) + messages_av[neighbor, v] = exp.(-beta * E_bond) * messages_va[neighbor, v] + end + end + + for v in vertices(fg) + E_local = get_prop(fg, v, :spectrum).energies + beliefs[v] = exp.(-E_local * beta) + for neighbor in get_neighbors(fg, v) + #update beliefs + pl = has_edge(fg, neighbor, v) ? get_prop(fg, neighbor, v, :pr) : get_prop(fg, v, neighbor, :pl) + beliefs[v] .*= messages_av[neighbor, v][pl] + end + # Normalize the beliefs + beliefs[v] = -log.(beliefs[v])./beta + beliefs[v] = beliefs[v] .- minimum(beliefs[v]) + end + + # Check convergence + converged = all([all(abs.(old_beliefs[v] .- beliefs[v]) .< tol) for v in keys(beliefs)]) + end + + output_message ? (beliefs, messages_av) : beliefs +end \ No newline at end of file diff --git a/test/bp_pegasus.jl b/test/bp_pegasus.jl index 207b593..3dc7f90 100644 --- a/test/bp_pegasus.jl +++ b/test/bp_pegasus.jl @@ -205,7 +205,8 @@ end push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) end for v in keys(beliefs) - @test beliefs[v] ≈ exact_marginal[v] + temp = -log.(exact_marginal[v])./beta + @test beliefs[v] ≈ temp .- minimum(temp) end end @testset "Belief propagation " begin @@ -218,8 +219,8 @@ end push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) end for v in keys(beliefs) - @test beliefs[v] ≈ exact_marginal[v] - end + temp = -log.(exact_marginal[v])./beta + @test beliefs[v] ≈ temp .- minimum(temp) end end @testset "Belief propagation pathological" begin ig, fg = create_larger_example_factor_graph_tree_pathological() @@ -231,34 +232,34 @@ end push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) end for v in keys(beliefs) - @test beliefs[v] ≈ exact_marginal[v] - end + temp = -log.(exact_marginal[v])./beta + @test beliefs[v] ≈ temp .- minimum(temp) end end -@testset "Belief propagation 2site" begin - ig, fg = create_larger_example_factor_graph_tree_2site() - beta = 1 - tol = 1e-12 - iter = 100 - beliefs, messages_av = belief_propagation(fg, beta; iter=iter, tol=tol, output_message=true) - exact_marginal = Dict() - for k in keys(beliefs) - push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) - end - for v in keys(beliefs) - @test beliefs[v] ≈ exact_marginal[v] - end - - for v in vertices(fg) - println("v ", v) - i, j, _ = v - n1, n2 = length(beliefs[(i, j, 1)]), length(beliefs[(i, j, 2)]) - exact = [exact_cond_prob(fg, beta, Dict((i, j, 1) => k1, (i, j, 2) => k2)) for k1 in 1:n1, k2 in 1:n2] - println("exact ", exact) - belief = beliefs_2site(fg, i, j, messages_av, beta) - println("belief ", belief) - - # @test beliefs_2site(fg, i, j, messages_av, beta) ≈ exact - end - -end \ No newline at end of file +# @testset "Belief propagation 2site" begin +# ig, fg = create_larger_example_factor_graph_tree_2site() +# beta = 1 +# tol = 1e-12 +# iter = 100 +# beliefs, messages_av = belief_propagation_old(fg, beta; iter=iter, tol=tol, output_message=true) +# exact_marginal = Dict() +# for k in keys(beliefs) +# push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) +# end +# for v in keys(beliefs) +# @test beliefs[v] ≈ exact_marginal[v] +# end + +# for v in vertices(fg) +# println("v ", v) +# i, j, _ = v +# n1, n2 = length(beliefs[(i, j, 1)]), length(beliefs[(i, j, 2)]) +# exact = [exact_cond_prob(fg, beta, Dict((i, j, 1) => k1, (i, j, 2) => k2)) for k1 in 1:n1, k2 in 1:n2] +# println("exact ", exact) +# belief = beliefs_2site(fg, i, j, messages_av, beta) +# println("belief ", belief) + +# # @test beliefs_2site(fg, i, j, messages_av, beta) ≈ exact +# end + +# end \ No newline at end of file From c1585d3d77e02631d5c926312cc8e701277ed3be Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 20 Jul 2023 11:37:20 +0200 Subject: [PATCH 149/218] BP 2-site --- Project.toml | 2 + src/SpinGlassNetworks.jl | 1 + src/factor.jl | 186 +++++++++++++++++++++++++--- test/{bp_pegasus.jl => bp_1site.jl} | 54 +------- test/bp_2site.jl | 103 +++++++++++++++ test/runtests.jl | 9 +- 6 files changed, 279 insertions(+), 76 deletions(-) rename test/{bp_pegasus.jl => bp_1site.jl} (82%) create mode 100644 test/bp_2site.jl diff --git a/Project.toml b/Project.toml index 3cc4808..c8d2678 100644 --- a/Project.toml +++ b/Project.toml @@ -11,6 +11,8 @@ LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2" MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5" +TensorCast = "02d47bb6-7ce6-556a-be16-bb1710789e2b" +TensorOperations = "6aa20fa7-93e2-5fca-9bc0-fbd0db3c71a2" [compat] CSV = "0.8" diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 0a0f097..0e24e82 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -6,6 +6,7 @@ module SpinGlassNetworks using DocStringExtensions using LinearAlgebra, MKL using Base.Cartesian + using TensorOperations, TensorCast import Base.Prehashed diff --git a/src/factor.jl b/src/factor.jl index 828aba9..08dd447 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -8,10 +8,12 @@ export cluster_size, truncate_factor_graph_2site_energy, truncate_factor_graph_1site_BP, + truncate_factor_graph_2site_BP, belief_propagation, belief_propagation_old, exact_cond_prob, - beliefs_2site + beliefs_2site, + factor_graph_2site """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ @@ -161,6 +163,21 @@ function truncate_factor_graph_2site_energy(fg::LabelledGraph{S, T}, num_states: truncate_factor_graph(fg, states) end +function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 + new_fg = factor_graph_2site(fg, beta) + beliefs = belief_propagation(new_fg, beta; tol, iter) + states = Dict() + for node in vertices(fg) + if node in keys(states) continue end + i, j, _ = node + sx = length(get_prop(fg, (i, j, 1), :spectrum).energies) + E = beliefs[(i,j)] + ind1, ind2 = select_numstate_best(E, sx, num_states) + push!(states, (i, j, 1) => ind1) + push!(states, (i, j, 2) => ind2) + end + truncate_factor_graph(fg, states) +end # truncate based on energy in two nodes of factor graph; resulting states are a product of states in two nodes, so we have to fine-tune to end up with expected number of states function select_numstate_best(E, sx, num_states) @@ -240,23 +257,23 @@ function truncate_factor_graph_1site_BP(fg::LabelledGraph{S, T}, num_states::Int truncate_factor_graph(fg, states) end -function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} - states = Dict() - beliefs, messages_av = belief_propagation(fg, beta; tol=tol, iter=iter, output_message=true) +# function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} +# states = Dict() +# beliefs, messages_av = belief_propagation(fg, beta; tol=tol, iter=iter, output_message=true) - for node in vertices(fg) - if node in keys(states) continue end - i, j, _ = node - temp = beliefs_2site(fg, i, j, messages_av, beta) - sx, sy = size(temp) - temp = reshape(temp, sx * sy) - ind1, ind2 = select_numstate_best(temp, sx, num_states) - push!(states, (i, j, 1) => ind1) - push!(states, (i, j, 2) => ind2) - end +# for node in vertices(fg) +# if node in keys(states) continue end +# i, j, _ = node +# temp = beliefs_2site(fg, i, j, messages_av, beta) +# sx, sy = size(temp) +# temp = reshape(temp, sx * sy) +# ind1, ind2 = select_numstate_best(temp, sx, num_states) +# push!(states, (i, j, 1) => ind1) +# push!(states, (i, j, 2) => ind2) +# end - truncate_factor_graph(fg, states) -end +# truncate_factor_graph(fg, states) +# end function beliefs_2site(fg::LabelledGraph{S, T}, i::Int, j::Int, messages_av::Dict, beta::Real) where {S, T} temp = energy_2site(fg, i, j) @@ -410,7 +427,7 @@ function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state:: # Initialize messages with uniform probabilities for v in vertices(fg) - ns = length(get_prop(fg, v, :spectrum).states) + ns = length(get_prop(fg, v, :spectrum).energies) push!(beliefs, v => ones(ns)./ns) for neighbor in get_neighbors(fg, v) pr = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :pr) : get_prop(fg, neighbor, v, :pl) @@ -453,10 +470,10 @@ function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state:: end for v in vertices(fg) for neighbor in get_neighbors(fg, v) - #update messages from edge to vertex + #update messages from edge to verte + # messages_av[neighbor, v] = exp.(-beta * E_bond) * messages_va[neighbor, v] E_bond = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :en) : get_prop(fg, neighbor, v, :en)' - E_bond = E_bond .- minimum(E_bond) - messages_av[neighbor, v] = exp.(-beta * E_bond) * messages_va[neighbor, v] + messages_av[neighbor, v] = update_message(messages_va[neighbor, v], E_bond, v, neighbor, beta) end end @@ -478,4 +495,133 @@ function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state:: end output_message ? (beliefs, messages_av) : beliefs +end + +struct Energy{T <: Real} + e11::AbstractMatrix{T} + e12::AbstractMatrix{T} + e21::AbstractMatrix{T} + e22::AbstractMatrix{T} +end + +Base.adjoint(s::Energy) = Energy(s.e11', s.e21', s.e12', s.e22') + +function update_message(message::Vector, E_bond, v, neighbor, beta) + E_bond = E_bond .- minimum(E_bond) + exp.(-beta * E_bond) * message +end + +function update_message(message::Vector, E_bond::Energy, v, neighbor, beta) + e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 + @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] + exp.(-beta * E) * message +end + +function unify_vertices(vertices::Vector{Tuple{Int64, Int64, Int64}}) + unified_vertices = Vector{Tuple{Int64, Int64}}() + for vertex in vertices + push!(unified_vertices, vertex[1:2]) + end + return unique(unified_vertices) +end + +function factor_graph_2site(fg::LabelledGraph{S, T}, beta::Real) where {S, T} + new_fg = LabelledGraph{MetaDiGraph}(unify_vertices(vertices(fg))) + + for v in vertices(fg) + i, j, _ = v + E1 = copy(get_prop(fg, (i, j, 1), :spectrum).energies) + E2 = copy(get_prop(fg, (i, j, 2), :spectrum).energies) + E = energy_2site(fg, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) + sp = Spectrum(reshape(E, :), []) + set_props!(new_fg, (i, j), Dict(:spectrum => sp)) + end + + edge_states = Set() + for e ∈ edges(fg) + if e in edge_states continue end + v, w = src(e), dst(e) + v1, v2, _ = v + w1, w2, _ = w + if (v1, v2) != (w1, w2) + add_edge!(new_fg, (v1, v2), (w1, w2)) + + E, pl, pr = merge_vertices(fg, beta, v, w) + push!(edge_states, sort([(v1, v2), (w1, w2)])) + + set_props!( + new_fg, (v1, v2), (w1, w2), Dict(:pl => pl, :en => E, :pr => pr) + ) + end + end + new_fg +end + +function merge_vertices(fg::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int64}, node2::NTuple{3, Int64} + ) where {S, T} + i1, j1, k1 = node1 + i2, j2, k2 = node2 + + p21l = projector(fg, (i1, j1, 2), (i2, j2, 1)) + p22l = projector(fg, (i1, j1, 2), (i2, j2, 2)) + p12l = projector(fg, (i1, j1, 1), (i2, j2, 2)) + p11l = projector(fg, (i1, j1, 1), (i2, j2, 1)) + + p1l, (p11l, p12l) = fuse_projectors((p11l, p12l)) + p2l, (p21l, p22l) = fuse_projectors((p21l, p22l)) + + p11r = projector(fg, (i2, j2, 1), (i1, j1, 1)) + p21r = projector(fg, (i2, j2, 1), (i1, j1, 2)) + p12r = projector(fg, (i2, j2, 2), (i1, j1, 1)) + p22r = projector(fg, (i2, j2, 2), (i1, j1, 2)) + + p1r, (p11r, p21r) = fuse_projectors((p11r, p21r)) + p2r, (p12r, p22r) = fuse_projectors((p12r, p22r)) + + pl = outer_projector(p1l, p2l) + pr = outer_projector(p1r, p2r) + + e11 = interaction_energy(fg, (i1, j1, 1), (i2, j2, 1)) + e12 = interaction_energy(fg, (i1, j1, 1), (i2, j2, 2)) + e21 = interaction_energy(fg, (i1, j1, 2), (i2, j2, 1)) + e22 = interaction_energy(fg, (i1, j1, 2), (i2, j2, 2)) + + e11 = e11[p11l, p11r] + e21 = e21[p21l, p21r] + e12 = e12[p12l, p12r] + e22 = e22[p22l, p22r] + + Energy(e11, e12, e21, e22), pl, pr +end + +function interaction_energy(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} + if has_edge(fg, w, v) + get_prop(fg, w, v, :en)' + elseif has_edge(fg, v, w) + get_prop(fg, v, w, :en) + else + zeros(1, 1) + end +end + +function projector(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} + if has_edge(fg, w, v) + p = get_prop(fg, w, v, :pr) + elseif has_edge(fg, v, w) + p = get_prop(fg, v, w, :pl) + else + p = ones(Int, v ∈ vertices(fg) ? length(get_prop(fg, v, :spectrum).energies) : 1) + end +end + +function fuse_projectors( + projectors::NTuple{N, K} + ) where {N, K} + fused, transitions_matrix = rank_reveal(hcat(projectors...), :PE) + transitions = Tuple(Array(t) for t ∈ eachcol(transitions_matrix)) + fused, transitions +end + +function outer_projector(p1::Array{T, 1}, p2::Array{T, 1}) where T <: Number + reshape(reshape(p1, :, 1) .+ maximum(p1) .* reshape(p2 .- 1, 1, :), :) end \ No newline at end of file diff --git a/test/bp_pegasus.jl b/test/bp_1site.jl similarity index 82% rename from test/bp_pegasus.jl rename to test/bp_1site.jl index 3dc7f90..c3c659f 100644 --- a/test/bp_pegasus.jl +++ b/test/bp_1site.jl @@ -142,57 +142,6 @@ function create_larger_example_factor_graph_tree_pathological() ig, fg end -""" -Instance below looks like this: - -1 -- 2 -| -3 -- 4 - -""" -function create_larger_example_factor_graph_tree_2site() - instance = Dict( - (1, 1) => 0.5, - (2, 2) => 0.25, - (3, 3) => 0.3, - (4, 4) => 0.1, - (5, 5) => 0.1, - (6, 6) => 0.1, - (7, 7) => 0.1, - (8, 8) => 0.1, - (1, 2) => -0.00001, - (1, 3) => 1.0, - (3, 4) => 1.0, - (2, 5) => 1.0, - (3, 4) => 1.0, - (6, 7) => 1.0, - (6, 8) => 1.0, - (6, 2) => 1.0 - ) - - ig = ising_graph(instance) - - assignment_rule = Dict( - 1 => (1, 1, 1), - 2 => (1, 1, 2), - 3 => (1, 2, 1), - 4 => (1, 2, 2), - 5 => (2, 1, 1), - 6 => (2, 1, 2), - 7 => (2, 2, 1), - 8 => (2, 2, 2) - ) - - fg = factor_graph( - ig, - Dict{NTuple{3, Int}, Int}(), - spectrum = full_spectrum, - cluster_assignment_rule = assignment_rule, - ) - - ig, fg -end - @testset "Belief propagation basic" begin @@ -209,6 +158,7 @@ end @test beliefs[v] ≈ temp .- minimum(temp) end end + @testset "Belief propagation " begin ig, fg = create_larger_example_factor_graph_tree() beta = 1 @@ -241,7 +191,7 @@ end # beta = 1 # tol = 1e-12 # iter = 100 -# beliefs, messages_av = belief_propagation_old(fg, beta; iter=iter, tol=tol, output_message=true) +# beliefs, messages_av = belief_propagation(fg, beta; iter=iter, tol=tol, output_message=true) # exact_marginal = Dict() # for k in keys(beliefs) # push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) diff --git a/test/bp_2site.jl b/test/bp_2site.jl new file mode 100644 index 0000000..9936fab --- /dev/null +++ b/test/bp_2site.jl @@ -0,0 +1,103 @@ +using TensorCast + +""" +Instance below looks like this: + +1 -- 2 +| +3 -- 4 + +""" +function create_larger_example_factor_graph_tree_2site() + instance = Dict( + (1, 1) => 0.5, + (2, 2) => 0.25, + (3, 3) => 0.3, + (4, 4) => 0.1, + (5, 5) => 0.1, + (6, 6) => 0.1, + (7, 7) => 0.1, + (8, 8) => 0.1, + (1, 2) => -0.00001, + (1, 3) => 1.0, + (3, 4) => 1.0, + (2, 5) => 1.0, + (6, 7) => 1.0, + (6, 8) => 1.0, + (6, 2) => 1.0 + ) + + ig = ising_graph(instance) + + assignment_rule1 = Dict( + 1 => (1, 1), + 2 => (1, 1), + 3 => (1, 2), + 4 => (1, 2), + 5 => (2, 1), + 6 => (2, 1), + 7 => (2, 2), + 8 => (2, 2) + ) + + assignment_rule2 = Dict( + 1 => (1, 1, 1), + 2 => (1, 1, 2), + 3 => (1, 2, 1), + 4 => (1, 2, 2), + 5 => (2, 1, 1), + 6 => (2, 1, 2), + 7 => (2, 2, 1), + 8 => (2, 2, 2) + ) + + fg1 = factor_graph( + ig, + Dict{NTuple{2, Int}, Int}(), + spectrum = full_spectrum, + cluster_assignment_rule = assignment_rule1, + ) + + fg2 = factor_graph( + ig, + Dict{NTuple{3, Int}, Int}(), + spectrum = full_spectrum, + cluster_assignment_rule = assignment_rule2, + ) + + ig, fg1, fg2 +end + + +@testset "Belief propagation 2site" begin + ig, fg1, fg2 = create_larger_example_factor_graph_tree_2site() + beta = 1 + tol = 1e-12 + iter = 100 + num_states=10 + new_fg1 = factor_graph_2site(fg2, beta) + @test vertices(new_fg1) == vertices(fg1) + @test edges(new_fg1) == edges(fg1) + for e ∈ vertices(new_fg1) + @test get_prop(new_fg1, e, :spectrum).energies ≈ get_prop(fg1, e, :spectrum).energies + end + for e ∈ edges(new_fg1) + E = get_prop(new_fg1, src(e), dst(e), :en) + @cast E[(l1, l2), (r1, r2)] := E.e11[l1, r1] + E.e21[l2, r1] + E.e12[l1, r2] + E.e22[l2, r2] + @test E == get_prop(fg1, src(e), dst(e), :en) + end + for e ∈ edges(new_fg1) + @test get_prop(new_fg1, src(e), dst(e), :pl) == get_prop(fg1, src(e), dst(e), :pl) + @test get_prop(new_fg1, src(e), dst(e), :pr) == get_prop(fg1, src(e), dst(e), :pr) + end + beliefs = belief_propagation(new_fg1, beta; iter=iter, tol=tol, output_message=false) + exact_marginal = Dict() + for k in keys(beliefs) + temp = -1/beta .* log.([exact_cond_prob(fg1, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + push!(exact_marginal, k => temp .- minimum(temp)) + end + for v in keys(beliefs) + @test beliefs[v] ≈ exact_marginal[v] + end + truncate_factor_graph_2site_BP(fg2, num_states; beta=beta, iter=iter) + end \ No newline at end of file diff --git a/test/runtests.jl b/test/runtests.jl index a4bc0b0..8571b3d 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -27,10 +27,11 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) end my_tests = [ - # "ising.jl", - # "factor.jl", - # "utils.jl", - "bp_pegasus.jl" + "ising.jl", + "factor.jl", + "utils.jl", + "bp_1site.jl", + "bp_2site.jl" ] for my_test ∈ my_tests From b4ce768340687173d50288f179d29dd2f5118c12 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Thu, 20 Jul 2023 15:57:12 +0200 Subject: [PATCH 150/218] rewrite update message, add tests --- src/factor.jl | 43 ++++++++++++++++-- test/bp_2site.jl | 112 ++++++++++++++++++++++++++++++++++++++++++++++- 2 files changed, 151 insertions(+), 4 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index 08dd447..dfa1633 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -511,10 +511,47 @@ function update_message(message::Vector, E_bond, v, neighbor, beta) exp.(-beta * E_bond) * message end +# function update_message(message::Vector, E_bond::Energy, v, neighbor, beta) +# e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 +# @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] +# exp.(-beta * E) * message +# end + function update_message(message::Vector, E_bond::Energy, v, neighbor, beta) - e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 - @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] - exp.(-beta * E) * message + e11, e12, e21, e22 = E_bond.e11', E_bond.e21', E_bond.e12', E_bond.e22' + sbt = length(message) + sl1, sl2, sr1, sr2 = size(e11, 1), size(e22, 1), size(e11, 2), size(e22, 2) + sinter = sbt * max(sl1 * sl2 * min(sr1, sr2), sr1 * sr2 * min(sl1, sl2)) + if sl1 * sl2 * sr1 * sr2 < sinter + e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 + @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] + return exp.(-beta * E) * message + elseif sr1 <= sr2 && sl1 <= sl2 + message = message' + message = message .* (exp.(-beta * e21))' + message = message * (exp.(-beta * e22)) + message .*= (exp.(-beta * e11)) + message .*= (exp.(-beta * e12)) + elseif sr1 <= sr2 && sl2 <= sl1 + message = message' + message = message .* (exp.(-beta * e11))' + message = message * (exp.(-beta * e12)) + message .*= (exp.(-beta * e21)) + message .*= (exp.(-beta * e22)) + elseif sr2 <= sr1 && sl1 <= sl2 + message = message' + message = message .* (exp.(-beta * e22))' + message = message * (exp.(-beta * e21)) + message .*= (exp.(-beta * e11)) + message .*= (exp.(-beta * e12)) + else # sr2 <= sr1 && sl2 <= sl1 + message = message' + message = message .* (exp.(-beta * e12))' + message = message * (exp.(-beta * e11)) + message .*= (exp.(-beta * e21)) + message .*= (exp.(-beta * e22)) + end + reshape(message, sr1 * sr2) end function unify_vertices(vertices::Vector{Tuple{Int64, Int64, Int64}}) diff --git a/test/bp_2site.jl b/test/bp_2site.jl index 9936fab..0836ee4 100644 --- a/test/bp_2site.jl +++ b/test/bp_2site.jl @@ -68,6 +68,83 @@ function create_larger_example_factor_graph_tree_2site() ig, fg1, fg2 end +""" +Instance below looks like this: + +1 -- 2 -- 3 + | + 4 + | + 5 + +""" +function create_larger_example_factor_graph_tree_2site_pathological() + instance = Dict( + (1, 1) => 0.5, + (2, 2) => 0.25, + (3, 3) => 0.3, + (4, 4) => 0.1, + (5, 5) => 0.1, + (6, 6) => 0.1, + (7, 7) => 0.1, + (8, 8) => 0.1, + (9, 9) => 0.001, + (10, 10) => -0.5, + (1, 2) => -0.00001, + (1, 3) => 1.0, + (3, 4) => 1.0, + (4, 6) => 1.0, + (5, 8) => 1.0, + (7, 10) => 1.0, + (8, 9) => 1.0, + (9, 10) => -0.6 + ) + + ig = ising_graph(instance) + + assignment_rule1 = Dict( + 1 => (1, 1), + 2 => (1, 1), + 3 => (1, 2), + 4 => (1, 2), + 5 => (1, 3), + 6 => (1, 3), + 7 => (2, 2), + 8 => (2, 2), + 9 => (3, 2), + 10 => (3, 2) + ) + + assignment_rule2 = Dict( + 1 => (1, 1, 1), + 2 => (1, 1, 2), + 3 => (1, 2, 1), + 4 => (1, 2, 2), + 5 => (1, 3, 1), + 6 => (1, 3, 2), + 7 => (2, 2, 1), + 8 => (2, 2, 2), + 9 => (3, 2, 1), + 10 => (3, 2, 2) + ) + + fg1 = factor_graph( + ig, + Dict{NTuple{2, Int}, Int}(), + spectrum = full_spectrum, + cluster_assignment_rule = assignment_rule1, + ) + + fg2 = factor_graph( + ig, + Dict{NTuple{3, Int}, Int}(), + spectrum = full_spectrum, + cluster_assignment_rule = assignment_rule2, + ) + + ig, fg1, fg2 +end + @testset "Belief propagation 2site" begin ig, fg1, fg2 = create_larger_example_factor_graph_tree_2site() @@ -100,4 +177,37 @@ end @test beliefs[v] ≈ exact_marginal[v] end truncate_factor_graph_2site_BP(fg2, num_states; beta=beta, iter=iter) - end \ No newline at end of file + end + + @testset "Belief propagation 2site pathological" begin + ig, fg1, fg2 = create_larger_example_factor_graph_tree_2site_pathological() + beta = 1 + tol = 1e-12 + iter = 100 + num_states=10 + new_fg1 = factor_graph_2site(fg2, beta) + @test vertices(new_fg1) == vertices(fg1) + @test edges(new_fg1) == edges(fg1) + for e ∈ vertices(new_fg1) + @test get_prop(new_fg1, e, :spectrum).energies ≈ get_prop(fg1, e, :spectrum).energies + end + for e ∈ edges(new_fg1) + E = get_prop(new_fg1, src(e), dst(e), :en) + @cast E[(l1, l2), (r1, r2)] := E.e11[l1, r1] + E.e21[l2, r1] + E.e12[l1, r2] + E.e22[l2, r2] + @test E == get_prop(fg1, src(e), dst(e), :en) + end + for e ∈ edges(new_fg1) + @test get_prop(new_fg1, src(e), dst(e), :pl) == get_prop(fg1, src(e), dst(e), :pl) + @test get_prop(new_fg1, src(e), dst(e), :pr) == get_prop(fg1, src(e), dst(e), :pr) + end + beliefs = belief_propagation(new_fg1, beta; iter=iter, tol=tol, output_message=false) + exact_marginal = Dict() + for k in keys(beliefs) + temp = -1/beta .* log.([exact_cond_prob(fg1, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + push!(exact_marginal, k => temp .- minimum(temp)) + end + for v in keys(beliefs) + @test beliefs[v] ≈ exact_marginal[v] + end + truncate_factor_graph_2site_BP(fg2, num_states; beta=beta, iter=iter) +end \ No newline at end of file From 592037d41f6e62adda095cfb6eb1cb8c451e66fb Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 21 Jul 2023 10:20:00 +0200 Subject: [PATCH 151/218] bp (pathological not working) --- src/factor.jl | 116 ++++++++--------------------- test/bp_1site.jl | 173 +++++++++++++++----------------------------- test/bp_2site.jl | 185 +++++++++++++++++++++-------------------------- 3 files changed, 170 insertions(+), 304 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index dfa1633..de8bdd8 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -219,7 +219,7 @@ end function truncate_factor_graph(fg::LabelledGraph{S, T}, states::Dict) where {S, T} new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) - + for v ∈ vertices(new_fg) cl = get_prop(fg, v, :cluster) sp = get_prop(fg, v, :spectrum) @@ -257,29 +257,12 @@ function truncate_factor_graph_1site_BP(fg::LabelledGraph{S, T}, num_states::Int truncate_factor_graph(fg, states) end -# function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} -# states = Dict() -# beliefs, messages_av = belief_propagation(fg, beta; tol=tol, iter=iter, output_message=true) - -# for node in vertices(fg) -# if node in keys(states) continue end -# i, j, _ = node -# temp = beliefs_2site(fg, i, j, messages_av, beta) -# sx, sy = size(temp) -# temp = reshape(temp, sx * sy) -# ind1, ind2 = select_numstate_best(temp, sx, num_states) -# push!(states, (i, j, 1) => ind1) -# push!(states, (i, j, 2) => ind2) -# end - -# truncate_factor_graph(fg, states) -# end function beliefs_2site(fg::LabelledGraph{S, T}, i::Int, j::Int, messages_av::Dict, beta::Real) where {S, T} temp = energy_2site(fg, i, j) temp = exp.(-beta*temp) if ((i, j, 1), (i, j, 2)) in keys(messages_av) - temp = temp .* reshape(messages_av[(i, j, 1), (i, j, 2)], :, 1) + temp = temp .* reshape(messages_av[(i, j, 1), (i, j, 2)], :, 1) temp = temp .*reshape(messages_av[(i, j, 2), (i, j, 1)], 1, :) end temp ./= sum(temp) @@ -302,47 +285,6 @@ function energy_2site(fg::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} int_eng end -# Works for Pegasus and Zephyr -# function truncate_factor_graph_1site(fg::LabelledGraph{S, T}, beta::Real, num_states::Int; tol=1e-6, iter=1) where {S, T} -# states = Dict() -# beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) - -# # Truncate the state space based on the belief probabilities -# for node in vertices(fg) -# indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node])), rev=true) -# push!(states, node => indices) -# end - -# # Create a new factor graph with truncated state space -# new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) - -# for v ∈ vertices(new_fg) -# cl = get_prop(fg, v, :cluster) -# sp = get_prop(fg, v, :spectrum) -# sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) -# set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) -# end - -# for e ∈ edges(fg) -# v, w = src(e), dst(e) -# add_edge!(new_fg, v, w) -# outer_edges = get_prop(fg, v, w, :outer_edges) -# pl = get_prop(fg, v, w, :pl) -# pr = get_prop(fg, v, w, :pr) -# en = get_prop(fg, v, w, :en) -# pl = pl[states[v]] -# pr = pr[states[w]] -# pl_transition, pl_unique = rank_reveal(pl, :PE) -# pr_transition, pr_unique = rank_reveal(pr, :PE) -# en = en[pl_unique, pr_unique] - -# set_props!( -# new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) -# ) -# end -# new_fg -# end - function belief_propagation_old(fg, beta; tol=1e-6, iter=1, output_message=false) messages_va = Dict() @@ -357,7 +299,7 @@ function belief_propagation_old(fg, beta; tol=1e-6, iter=1, output_message=false push!(messages_va, (v, neighbor) => ones(ns)./ns) push!(messages_av, (neighbor, v) => ones(ns)./ns) end - end + end # Perform message passing until convergence converged = false @@ -391,7 +333,7 @@ function belief_propagation_old(fg, beta; tol=1e-6, iter=1, output_message=false messages_av[neighbor, v] ./= sum(messages_av[neighbor, v]) end end - + for v in vertices(fg) E_local = get_prop(fg, v, :spectrum).energies beliefs[v] = exp.(-E_local * beta) @@ -420,7 +362,7 @@ function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state:: sum(prob[findall([all(s[k] == v for (k, v) ∈ target_state) for s ∈ states])]) end - function belief_propagation(fg, beta; tol=1e-6, iter=1, output_message=false) + function belief_propagation(fg, beta; tol=1e-6, iter=1) messages_va = Dict() messages_av = Dict() beliefs = Dict() @@ -439,7 +381,7 @@ function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state:: push!(messages_va, (v, neighbor) => temp ./ sum(temp)) push!(messages_av, (neighbor, v) => ones(maximum(pl))) end - end + end # Perform message passing until convergence converged = false @@ -473,10 +415,10 @@ function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state:: #update messages from edge to verte # messages_av[neighbor, v] = exp.(-beta * E_bond) * messages_va[neighbor, v] E_bond = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :en) : get_prop(fg, neighbor, v, :en)' - messages_av[neighbor, v] = update_message(messages_va[neighbor, v], E_bond, v, neighbor, beta) + messages_av[neighbor, v] = update_message(messages_va[neighbor, v], E_bond, beta) end end - + for v in vertices(fg) E_local = get_prop(fg, v, :spectrum).energies beliefs[v] = exp.(-E_local * beta) @@ -494,10 +436,10 @@ function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state:: converged = all([all(abs.(old_beliefs[v] .- beliefs[v]) .< tol) for v in keys(beliefs)]) end - output_message ? (beliefs, messages_av) : beliefs + beliefs end -struct Energy{T <: Real} +struct Energy{T <: Real} e11::AbstractMatrix{T} e12::AbstractMatrix{T} e21::AbstractMatrix{T} @@ -506,18 +448,18 @@ end Base.adjoint(s::Energy) = Energy(s.e11', s.e21', s.e12', s.e22') -function update_message(message::Vector, E_bond, v, neighbor, beta) +function update_message(message::Vector, E_bond::Matrix, beta::Real) E_bond = E_bond .- minimum(E_bond) exp.(-beta * E_bond) * message end -# function update_message(message::Vector, E_bond::Energy, v, neighbor, beta) +# function update_message(message::Vector, E_bond::Energy, beta::Real) # e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 # @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] # exp.(-beta * E) * message # end -function update_message(message::Vector, E_bond::Energy, v, neighbor, beta) +function update_message(message::Vector, E_bond::Energy, beta::Real) e11, e12, e21, e22 = E_bond.e11', E_bond.e21', E_bond.e12', E_bond.e22' sbt = length(message) sl1, sl2, sr1, sr2 = size(e11, 1), size(e22, 1), size(e11, 2), size(e22, 2) @@ -525,31 +467,31 @@ function update_message(message::Vector, E_bond::Energy, v, neighbor, beta) if sl1 * sl2 * sr1 * sr2 < sinter e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] - return exp.(-beta * E) * message + return exp.(-beta * E) * message elseif sr1 <= sr2 && sl1 <= sl2 message = message' - message = message .* (exp.(-beta * e21))' - message = message * (exp.(-beta * e22)) - message .*= (exp.(-beta * e11)) + message = message .* (exp.(-beta * e21))' + message = message * (exp.(-beta * e22)) + message .*= (exp.(-beta * e11)) message .*= (exp.(-beta * e12)) elseif sr1 <= sr2 && sl2 <= sl1 message = message' - message = message .* (exp.(-beta * e11))' - message = message * (exp.(-beta * e12)) - message .*= (exp.(-beta * e21)) + message = message .* (exp.(-beta * e11))' + message = message * (exp.(-beta * e12)) + message .*= (exp.(-beta * e21)) message .*= (exp.(-beta * e22)) elseif sr2 <= sr1 && sl1 <= sl2 message = message' - message = message .* (exp.(-beta * e22))' - message = message * (exp.(-beta * e21)) - message .*= (exp.(-beta * e11)) + message = message .* (exp.(-beta * e22))' + message = message * (exp.(-beta * e21)) + message .*= (exp.(-beta * e11)) message .*= (exp.(-beta * e12)) else # sr2 <= sr1 && sl2 <= sl1 message = message' - message = message .* (exp.(-beta * e12))' - message = message * (exp.(-beta * e11)) - message .*= (exp.(-beta * e21)) - message .*= (exp.(-beta * e22)) + message = message .* (exp.(-beta * e12))' + message = message * (exp.(-beta * e11)) + message .*= (exp.(-beta * e21)) + message .*= (exp.(-beta * e22)) end reshape(message, sr1 * sr2) end @@ -580,9 +522,9 @@ function factor_graph_2site(fg::LabelledGraph{S, T}, beta::Real) where {S, T} v, w = src(e), dst(e) v1, v2, _ = v w1, w2, _ = w - if (v1, v2) != (w1, w2) + if (v1, v2) != (w1, w2) add_edge!(new_fg, (v1, v2), (w1, w2)) - + E, pl, pr = merge_vertices(fg, beta, v, w) push!(edge_states, sort([(v1, v2), (w1, w2)])) diff --git a/test/bp_1site.jl b/test/bp_1site.jl index c3c659f..756384a 100644 --- a/test/bp_1site.jl +++ b/test/bp_1site.jl @@ -8,13 +8,13 @@ Instance below looks like this: """ function create_larger_example_factor_graph_tree_basic() instance = Dict( - (1, 1) => 0.5, - (2, 2) => 0.25, - (3, 3) => 0.3, - (4, 4) => 0.1, - (1, 2) => -1.0, - (1, 3) => 1.0, - (3, 4) => 1.0 + (1, 1) => -0.50, + (2, 2) => 0.25, + (3, 3) => -0.30, + (4, 4) => 0.10, + (1, 2) => -0.23, + (1, 3) => 1.10, + (3, 4) => 0.71 ) ig = ising_graph(instance) @@ -42,28 +42,27 @@ Instance below looks like this: 1 -- 2 -- 3 | 4 -- 5 -- 6 -| +| 7 -- 8 -- 9 """ function create_larger_example_factor_graph_tree() instance = Dict( - (1, 1) => 0.5, - (2, 2) => 0.25, - (3, 3) => 0.3, - (4, 4) => 0.1, - (5, 5) => -0.1, - (6, 6) => 0.1, - (7, 7) => 0.0, - (8, 8) => 0.1, - (9, 9) => 0.01, - (1, 2) => -1.0, - (2, 3) => 1.0, - (1, 4) => 1.0, - (4, 5) => 1.0, - (5, 6) => 1.0, - (4, 7) => 1.0, - (7, 8) => 1.0, - (8, 9) => 1.0 + (1, 1) => 0.53, + (2, 2) => -0.25, + (3, 3) => 0.30, + (4, 4) => -0.10, + (5, 5) => -0.10, + (6, 6) => 0.10, + (8, 8) => 0.10, + (9, 9) => 0.01, + (1, 2) => -1.00, + (2, 3) => 1.00, + (1, 4) => 0.33, + (4, 5) => 0.76, + (5, 6) => -0.45, + (4, 7) => -0.28, + (7, 8) => 0.36, + (8, 9) => -1.07 ) ig = ising_graph(instance) @@ -93,30 +92,29 @@ end """ Instance below looks like this: -1 -- 2 -- 3 -| | -4 5 +123 -- 45 -- 6 +| | +7 8 """ function create_larger_example_factor_graph_tree_pathological() instance = Dict( - (1, 1) => 0.5, - (2, 2) => 0.25, - (3, 3) => 0.3, - (4, 4) => 0.1, - (5, 5) => -0.1, - (6, 6) => 0.1, - (7, 7) => 0.0, - (8, 8) => 0.1, - (1, 2) => -1.0, - (1, 3) => 1.0, - (3, 4) => 1.0, - (3, 5) => 1.0, - (5, 6) => 1.0, - (2, 7) => 0.5, - (3, 7) => 1.0, - (5, 8) => 1.0, - + (1, 1) => 0.52, + (2, 2) => 0.25, + (3, 3) => -0.31, + (4, 4) => 0.17, + (5, 5) => -0.12, + (6, 6) => 0.13, + (7, 7) => 0.00, + (8, 8) => 0.43, + (1, 2) => -1.01, + (1, 3) => 1.00, + (3, 4) => 0.97, + (3, 5) => -0.98, + (5, 6) => 1.00, + (2, 7) => 0.53, + (3, 7) => 1.06, + (5, 8) => -0.64, ) ig = ising_graph(instance) @@ -142,74 +140,21 @@ function create_larger_example_factor_graph_tree_pathological() ig, fg end - - -@testset "Belief propagation basic" begin - ig, fg = create_larger_example_factor_graph_tree_basic() - beta = 1 - iter = 100 - beliefs = belief_propagation(fg, beta; iter=iter) - exact_marginal = Dict() - for k in keys(beliefs) - push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) - end - for v in keys(beliefs) - temp = -log.(exact_marginal[v])./beta - @test beliefs[v] ≈ temp .- minimum(temp) +@testset "Belief propagation" begin + for (ig, fg) ∈ [create_larger_example_factor_graph_tree_basic(), + create_larger_example_factor_graph_tree(), + create_larger_example_factor_graph_tree_pathological()] + for beta ∈ [0.5, 1] + iter = 16 + beliefs = belief_propagation(fg, beta; iter=iter) + exact_marginal = Dict() + for k in keys(beliefs) + push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + end + for v in keys(beliefs) + temp = -log.(exact_marginal[v])./beta + @test beliefs[v] ≈ temp .- minimum(temp) + end + end end end - -@testset "Belief propagation " begin - ig, fg = create_larger_example_factor_graph_tree() - beta = 1 - iter = 100 - beliefs = belief_propagation(fg, beta; iter=iter) - exact_marginal = Dict() - for k in keys(beliefs) - push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) - end - for v in keys(beliefs) - temp = -log.(exact_marginal[v])./beta - @test beliefs[v] ≈ temp .- minimum(temp) end -end -@testset "Belief propagation pathological" begin - ig, fg = create_larger_example_factor_graph_tree_pathological() - beta = 1 - iter = 100 - beliefs = belief_propagation(fg, beta; iter=iter) - exact_marginal = Dict() - for k in keys(beliefs) - push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) - end - for v in keys(beliefs) - temp = -log.(exact_marginal[v])./beta - @test beliefs[v] ≈ temp .- minimum(temp) end -end - -# @testset "Belief propagation 2site" begin -# ig, fg = create_larger_example_factor_graph_tree_2site() -# beta = 1 -# tol = 1e-12 -# iter = 100 -# beliefs, messages_av = belief_propagation(fg, beta; iter=iter, tol=tol, output_message=true) -# exact_marginal = Dict() -# for k in keys(beliefs) -# push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) -# end -# for v in keys(beliefs) -# @test beliefs[v] ≈ exact_marginal[v] -# end - -# for v in vertices(fg) -# println("v ", v) -# i, j, _ = v -# n1, n2 = length(beliefs[(i, j, 1)]), length(beliefs[(i, j, 2)]) -# exact = [exact_cond_prob(fg, beta, Dict((i, j, 1) => k1, (i, j, 2) => k2)) for k1 in 1:n1, k2 in 1:n2] -# println("exact ", exact) -# belief = beliefs_2site(fg, i, j, messages_av, beta) -# println("belief ", belief) - -# # @test beliefs_2site(fg, i, j, messages_av, beta) ≈ exact -# end - -# end \ No newline at end of file diff --git a/test/bp_2site.jl b/test/bp_2site.jl index 0836ee4..0ef7cd1 100644 --- a/test/bp_2site.jl +++ b/test/bp_2site.jl @@ -3,28 +3,28 @@ using TensorCast """ Instance below looks like this: -1 -- 2 +12 -- 34 | -3 -- 4 +56 -- 78 """ function create_larger_example_factor_graph_tree_2site() instance = Dict( - (1, 1) => 0.5, - (2, 2) => 0.25, - (3, 3) => 0.3, - (4, 4) => 0.1, - (5, 5) => 0.1, - (6, 6) => 0.1, - (7, 7) => 0.1, - (8, 8) => 0.1, - (1, 2) => -0.00001, - (1, 3) => 1.0, - (3, 4) => 1.0, - (2, 5) => 1.0, - (6, 7) => 1.0, - (6, 8) => 1.0, - (6, 2) => 1.0 + (1, 1) => 0.50, + (2, 2) => -0.25, + (3, 3) => 0.30, + (4, 4) => -0.10, + (5, 5) => 0.10, + (6, 6) => 0.20, + (7, 7) => -0.40, + (8, 8) => 0.50, + (1, 2) => -0.01, + (1, 3) => 1.00, + (3, 4) => 1.10, + (2, 5) => 0.77, + (6, 7) => -1.43, + (6, 8) => 0.21, + (6, 2) => 1.00 ) ig = ising_graph(instance) @@ -80,24 +80,27 @@ Instance below looks like this: """ function create_larger_example_factor_graph_tree_2site_pathological() instance = Dict( - (1, 1) => 0.5, - (2, 2) => 0.25, - (3, 3) => 0.3, - (4, 4) => 0.1, - (5, 5) => 0.1, - (6, 6) => 0.1, - (7, 7) => 0.1, - (8, 8) => 0.1, - (9, 9) => 0.001, - (10, 10) => -0.5, - (1, 2) => -0.00001, - (1, 3) => 1.0, - (3, 4) => 1.0, - (4, 6) => 1.0, - (5, 8) => 1.0, - (7, 10) => 1.0, - (8, 9) => 1.0, - (9, 10) => -0.6 + (1, 1) => -0.50, + (2, 2) => 0.25, + (3, 3) => 0.31, + (4, 4) => 0.77, + (5, 5) => -0.15, + (6, 6) => 0.21, + (7, 7) => -0.10, + (8, 8) => 0.13, + (9, 9) => 0.01, + (10, 10) => 0.5, + (1, 2) => -0.01, + (1, 3) => 0.79, + (2, 5) => -0.93, + (5, 6) => 0.81, + (5, 9) => -0.17, + (3, 4) => 0.71, + (4, 6) => -0.43, + (5, 8) => 0.75, + (7, 10)=> -1.03, + (8, 9) => 0.65, + (9, 10)=> -0.57 ) ig = ising_graph(instance) @@ -107,11 +110,11 @@ function create_larger_example_factor_graph_tree_2site_pathological() 2 => (1, 1), 3 => (1, 2), 4 => (1, 2), - 5 => (1, 3), + 5 => (1, 2), 6 => (1, 3), 7 => (2, 2), 8 => (2, 2), - 9 => (3, 2), + 9 => (2, 2), 10 => (3, 2) ) @@ -119,12 +122,12 @@ function create_larger_example_factor_graph_tree_2site_pathological() 1 => (1, 1, 1), 2 => (1, 1, 2), 3 => (1, 2, 1), - 4 => (1, 2, 2), - 5 => (1, 3, 1), + 4 => (1, 2, 1), + 5 => (1, 2, 2), 6 => (1, 3, 2), 7 => (2, 2, 1), - 8 => (2, 2, 2), - 9 => (3, 2, 1), + 8 => (2, 2, 1), + 9 => (2, 2, 2), 10 => (3, 2, 2) ) @@ -147,67 +150,43 @@ end @testset "Belief propagation 2site" begin - ig, fg1, fg2 = create_larger_example_factor_graph_tree_2site() - beta = 1 - tol = 1e-12 - iter = 100 - num_states=10 - new_fg1 = factor_graph_2site(fg2, beta) - @test vertices(new_fg1) == vertices(fg1) - @test edges(new_fg1) == edges(fg1) - for e ∈ vertices(new_fg1) - @test get_prop(new_fg1, e, :spectrum).energies ≈ get_prop(fg1, e, :spectrum).energies - end - for e ∈ edges(new_fg1) - E = get_prop(new_fg1, src(e), dst(e), :en) - @cast E[(l1, l2), (r1, r2)] := E.e11[l1, r1] + E.e21[l2, r1] + E.e12[l1, r2] + E.e22[l2, r2] - @test E == get_prop(fg1, src(e), dst(e), :en) - end - for e ∈ edges(new_fg1) - @test get_prop(new_fg1, src(e), dst(e), :pl) == get_prop(fg1, src(e), dst(e), :pl) - @test get_prop(new_fg1, src(e), dst(e), :pr) == get_prop(fg1, src(e), dst(e), :pr) - end - beliefs = belief_propagation(new_fg1, beta; iter=iter, tol=tol, output_message=false) - exact_marginal = Dict() - for k in keys(beliefs) - temp = -1/beta .* log.([exact_cond_prob(fg1, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) - push!(exact_marginal, k => temp .- minimum(temp)) - end - for v in keys(beliefs) - @test beliefs[v] ≈ exact_marginal[v] - end - truncate_factor_graph_2site_BP(fg2, num_states; beta=beta, iter=iter) - end - @testset "Belief propagation 2site pathological" begin - ig, fg1, fg2 = create_larger_example_factor_graph_tree_2site_pathological() - beta = 1 - tol = 1e-12 - iter = 100 - num_states=10 - new_fg1 = factor_graph_2site(fg2, beta) - @test vertices(new_fg1) == vertices(fg1) - @test edges(new_fg1) == edges(fg1) - for e ∈ vertices(new_fg1) - @test get_prop(new_fg1, e, :spectrum).energies ≈ get_prop(fg1, e, :spectrum).energies - end - for e ∈ edges(new_fg1) - E = get_prop(new_fg1, src(e), dst(e), :en) - @cast E[(l1, l2), (r1, r2)] := E.e11[l1, r1] + E.e21[l2, r1] + E.e12[l1, r2] + E.e22[l2, r2] - @test E == get_prop(fg1, src(e), dst(e), :en) - end - for e ∈ edges(new_fg1) - @test get_prop(new_fg1, src(e), dst(e), :pl) == get_prop(fg1, src(e), dst(e), :pl) - @test get_prop(new_fg1, src(e), dst(e), :pr) == get_prop(fg1, src(e), dst(e), :pr) + for (ig, fg1, fg2) ∈ [create_larger_example_factor_graph_tree_2site(), + create_larger_example_factor_graph_tree_2site_pathological()] + for beta ∈ [0.6, 1.1] + tol = 1e-12 + iter = 16 + num_states=10 + + new_fg1 = factor_graph_2site(fg2, beta) + + @test vertices(new_fg1) == vertices(fg1) + @test edges(new_fg1) == edges(fg1) + for e ∈ vertices(new_fg1) + @test get_prop(new_fg1, e, :spectrum).energies ≈ get_prop(fg1, e, :spectrum).energies + end + for e ∈ edges(new_fg1) + E = get_prop(new_fg1, src(e), dst(e), :en) + @cast E[(l1, l2), (r1, r2)] := E.e11[l1, r1] + E.e21[l2, r1] + E.e12[l1, r2] + E.e22[l2, r2] + @test E == get_prop(fg1, src(e), dst(e), :en) + end + for e ∈ edges(new_fg1) + @test get_prop(new_fg1, src(e), dst(e), :pl) == get_prop(fg1, src(e), dst(e), :pl) + @test get_prop(new_fg1, src(e), dst(e), :pr) == get_prop(fg1, src(e), dst(e), :pr) + end + + beliefs = belief_propagation(new_fg1, beta; iter=iter, tol=tol, output_message=false) + + exact_marginal = Dict() + for k in keys(beliefs) + temp = -1/beta .* log.([exact_cond_prob(fg1, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + push!(exact_marginal, k => temp .- minimum(temp)) + end + for v in keys(beliefs) + @test beliefs[v] ≈ exact_marginal[v] + end + + truncate_factor_graph_2site_BP(fg2, num_states; beta=beta, iter=iter) + end end - beliefs = belief_propagation(new_fg1, beta; iter=iter, tol=tol, output_message=false) - exact_marginal = Dict() - for k in keys(beliefs) - temp = -1/beta .* log.([exact_cond_prob(fg1, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) - push!(exact_marginal, k => temp .- minimum(temp)) - end - for v in keys(beliefs) - @test beliefs[v] ≈ exact_marginal[v] - end - truncate_factor_graph_2site_BP(fg2, num_states; beta=beta, iter=iter) -end \ No newline at end of file + end From cb8b39e700ee08eb7f36f2cc9c250bfbca19f853 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 21 Jul 2023 11:55:13 +0200 Subject: [PATCH 152/218] bp example --- examples/bp.jl | 69 ++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 69 insertions(+) create mode 100644 examples/bp.jl diff --git a/examples/bp.jl b/examples/bp.jl new file mode 100644 index 0000000..879b861 --- /dev/null +++ b/examples/bp.jl @@ -0,0 +1,69 @@ +using SpinGlassNetworks +using LabelledGraphs +using LightGraphs +using MetaGraphs +using Logging + +""" +Instance below looks like this: + +1 -- 2 -- 3 +| +4 -- 5 -- 6 +| +7 -- 8 -- 9 +""" +function create_larger_example_factor_graph_tree() + instance = Dict( + (1, 1) => 0.5, + (2, 2) => 0.25, + (3, 3) => 0.3, + (4, 4) => 0.1, + (5, 5) => -0.1, + (6, 6) => 0.1, + (7, 7) => 0.0, + (8, 8) => 0.1, + (9, 9) => 0.01, + (1, 2) => -1.0, + (2, 3) => 1.0, + (1, 4) => 1.0, + (4, 5) => 1.0, + (5, 6) => 1.0, + (4, 7) => 1.0, + (7, 8) => 1.0, + (8, 9) => 1.0 + ) + + ig = ising_graph(instance) + + assignment_rule = Dict( + 1 => (1, 1, 1), + 2 => (1, 2, 1), + 3 => (1, 3, 1), + 4 => (2, 1, 1), + 5 => (2, 2, 1), + 6 => (2, 3, 1), + 7 => (3, 1, 1), + 8 => (3, 2, 1), + 9 => (3, 3, 1) + ) + + fg = factor_graph( + ig, + Dict{NTuple{3, Int}, Int}(), + spectrum = full_spectrum, + cluster_assignment_rule = assignment_rule, + ) + + ig, fg +end + +ig, fg = create_larger_example_factor_graph_tree() +beta = 1 +iter = 0 +beliefs = belief_propagation(fg, beta; iter=iter) +println(beliefs) +# for v in vertices(fg) +# println("vertex ", v) +# println(get_prop(fg, v, :spectrum).energies) +# end From 93c8d6d3950000cb7fd425d716e5ed152c687bee Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 21 Jul 2023 12:07:59 +0200 Subject: [PATCH 153/218] cleaning --- examples/bp.jl | 14 +- src/SpinGlassNetworks.jl | 2 + src/bp.jl | 260 ++++++++++++++++++++++ src/factor.jl | 455 +++------------------------------------ src/truncate.jl | 72 +++++++ test/bp_2site.jl | 12 +- test/runtests.jl | 6 +- 7 files changed, 375 insertions(+), 446 deletions(-) create mode 100644 src/bp.jl create mode 100644 src/truncate.jl diff --git a/examples/bp.jl b/examples/bp.jl index 879b861..2ecbad1 100644 --- a/examples/bp.jl +++ b/examples/bp.jl @@ -10,7 +10,7 @@ Instance below looks like this: 1 -- 2 -- 3 | 4 -- 5 -- 6 -| +| 7 -- 8 -- 9 """ function create_larger_example_factor_graph_tree() @@ -59,11 +59,11 @@ function create_larger_example_factor_graph_tree() end ig, fg = create_larger_example_factor_graph_tree() -beta = 1 +beta = 0.1 iter = 0 beliefs = belief_propagation(fg, beta; iter=iter) -println(beliefs) -# for v in vertices(fg) -# println("vertex ", v) -# println(get_prop(fg, v, :spectrum).energies) -# end + +for v in vertices(fg) + en = get_prop(fg, v, :spectrum).energies + println("vertex ", v, " energy = ", en .- minimum(en), " bp = ", beliefs[v]) +end diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 0e24e82..091ba36 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -89,5 +89,7 @@ module SpinGlassNetworks include("spectrum.jl") include("lattice.jl") include("factor.jl") + include("bp.jl") + include("truncate.jl") include("utils.jl") end # module diff --git a/src/bp.jl b/src/bp.jl new file mode 100644 index 0000000..8df7450 --- /dev/null +++ b/src/bp.jl @@ -0,0 +1,260 @@ + +export + belief_propagation, + factor_graph_2site + + +function belief_propagation(fg, beta; tol=1e-6, iter=1) + messages_ve = Dict() + messages_ev = Dict() + + # Initialize messages with uniform probabilities + for v in vertices(fg) + for neighbor in get_neighbors(fg, v) + pr = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :pr) : get_prop(fg, neighbor, v, :pl) + pl = has_edge(fg, neighbor, v) ? get_prop(fg, neighbor, v, :pr) : get_prop(fg, v, neighbor, :pl) + temp = zeros(maximum(pr)) + for (i, r) in enumerate(pr) + temp[r] += 1 + end + push!(messages_ve, (v, neighbor) => temp ./ sum(temp)) + push!(messages_ev, (neighbor, v) => ones(maximum(pl))) + end + end + + # Perform message passing until convergence + converged = false + iteration = 0 + while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold + iteration += 1 + old_messages_ve = deepcopy(messages_ve) + for v in vertices(fg) + for neighbor in get_neighbors(fg, v) + #update messages from vertex to edge + E_local = get_prop(fg, v, :spectrum).energies + E_local = E_local .- minimum(E_local) + messages_ve[v, neighbor] = exp.(-E_local * beta) + for n in get_neighbors(fg, v) + if n != neighbor + pl = has_edge(fg, n, v) ? get_prop(fg, n, v, :pr) : get_prop(fg, v, n, :pl) + messages_ve[v, neighbor] .*= messages_ev[n, v][pl] + end + end + messages_ve[v, neighbor] ./= sum(messages_ve[v, neighbor]) + pr = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :pl) : get_prop(fg, neighbor, v, :pr) + temp = zeros(maximum(pr)) + for (i, r) in enumerate(pr) + temp[r] += messages_ve[v, neighbor][i] + end + messages_ve[v, neighbor] = temp + end + end + for v in vertices(fg) + for neighbor in get_neighbors(fg, v) + #update messages from edge to verte + # messages_ev[neighbor, v] = exp.(-beta * E_bond) * messages_ve[neighbor, v] + E_bond = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :en) : get_prop(fg, neighbor, v, :en)' + messages_ev[neighbor, v] = update_message(messages_ve[neighbor, v], E_bond, beta) + end + end + + # Check convergence + # converged = all([all(abs.(old_messages_ve[v] .- messages_ve[v]) .< tol) for v in keys(messages_ve)]) + end + + beliefs = Dict() + for v in vertices(fg) + E_local = get_prop(fg, v, :spectrum).energies + beliefs[v] = exp.(-E_local * beta) + for neighbor in get_neighbors(fg, v) + #update beliefs + pl = has_edge(fg, neighbor, v) ? get_prop(fg, neighbor, v, :pr) : get_prop(fg, v, neighbor, :pl) + beliefs[v] .*= messages_ev[neighbor, v][pl] + end + # Normalize the beliefs + beliefs[v] = -log.(beliefs[v])./beta + beliefs[v] = beliefs[v] .- minimum(beliefs[v]) + end + + beliefs +end + + +function get_neighbors(graph::LabelledGraph{S, T}, vertex::NTuple) where {S, T} + neighbors = [] + for edge in edges(graph) + src_node, dst_node = src(edge), dst(edge) + if src_node == vertex + push!(neighbors, dst_node) + elseif dst_node == vertex + push!(neighbors, src_node) + end + end + return neighbors +end + +struct MergedEnergy{T <: Real} + e11::AbstractMatrix{T} + e12::AbstractMatrix{T} + e21::AbstractMatrix{T} + e22::AbstractMatrix{T} +end + +Base.adjoint(s::MergedEnergy) = MergedEnergy(s.e11', s.e21', s.e12', s.e22') + +function update_message(message::Vector, E_bond::AbstractArray, beta::Real) + E_bond = E_bond .- minimum(E_bond) + exp.(-beta * E_bond) * message +end + +function update_message(message::Vector, E_bond::MergedEnergy, beta::Real) + # equivalent to + # @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] + # exp.(-beta * E) * message + # but without creating large matrix E if not optimal + + e11, e12, e21, e22 = E_bond.e11', E_bond.e21', E_bond.e12', E_bond.e22' + sbt = length(message) + sl1, sl2, sr1, sr2 = size(e11, 1), size(e22, 1), size(e11, 2), size(e22, 2) + sinter = sbt * max(sl1 * sl2 * min(sr1, sr2), sr1 * sr2 * min(sl1, sl2)) + if sl1 * sl2 * sr1 * sr2 < sinter + e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 + @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] + return exp.(-beta * E) * message + elseif sr1 <= sr2 && sl1 <= sl2 + message = message' + message = message .* (exp.(-beta * e21))' + message = message * (exp.(-beta * e22)) + message .*= (exp.(-beta * e11)) + message .*= (exp.(-beta * e12)) + elseif sr1 <= sr2 && sl2 <= sl1 + message = message' + message = message .* (exp.(-beta * e11))' + message = message * (exp.(-beta * e12)) + message .*= (exp.(-beta * e21)) + message .*= (exp.(-beta * e22)) + elseif sr2 <= sr1 && sl1 <= sl2 + message = message' + message = message .* (exp.(-beta * e22))' + message = message * (exp.(-beta * e21)) + message .*= (exp.(-beta * e11)) + message .*= (exp.(-beta * e12)) + else # sr2 <= sr1 && sl2 <= sl1 + message = message' + message = message .* (exp.(-beta * e12))' + message = message * (exp.(-beta * e11)) + message .*= (exp.(-beta * e21)) + message .*= (exp.(-beta * e22)) + end + reshape(message, sr1 * sr2) +end + + +function factor_graph_2site(fg::LabelledGraph{S, T}, beta::Real) where {S, T} + + unified_vertices = unique([vertex[1:2] for vertex in vertices(fg)]) + new_fg = LabelledGraph{MetaDiGraph}(unified_vertices) + + vertx = Set() + for v in vertices(fg) + i, j, _ = v + if (i, j) ∈ vertx continue end + E1 = local_energy(fg, (i, j, 1)) + E2 = local_energy(fg, (i, j, 2)) + E = energy_2site(fg, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) + sp = Spectrum(reshape(E, :), []) + set_props!(new_fg, (i, j), Dict(:spectrum => sp)) + push!(vertx, (i, j)) + end + + edge_states = Set() + for e ∈ edges(fg) + if e in edge_states continue end + v, w = src(e), dst(e) + v1, v2, _ = v + w1, w2, _ = w + + if (v1, v2) == (w1, w2) continue end + + add_edge!(new_fg, (v1, v2), (w1, w2)) + + E, pl, pr = merge_vertices(fg, beta, v, w) + set_props!(new_fg, (v1, v2), (w1, w2), Dict(:pl => pl, :en => E, :pr => pr)) + push!(edge_states, sort([(v1, v2), (w1, w2)])) + end + new_fg +end + +function merge_vertices(fg::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int64}, node2::NTuple{3, Int64} + ) where {S, T} + i1, j1, k1 = node1 + i2, j2, k2 = node2 + + p21l = projector(fg, (i1, j1, 2), (i2, j2, 1)) + p22l = projector(fg, (i1, j1, 2), (i2, j2, 2)) + p12l = projector(fg, (i1, j1, 1), (i2, j2, 2)) + p11l = projector(fg, (i1, j1, 1), (i2, j2, 1)) + + p1l, (p11l, p12l) = fuse_projectors((p11l, p12l)) + p2l, (p21l, p22l) = fuse_projectors((p21l, p22l)) + + p11r = projector(fg, (i2, j2, 1), (i1, j1, 1)) + p21r = projector(fg, (i2, j2, 1), (i1, j1, 2)) + p12r = projector(fg, (i2, j2, 2), (i1, j1, 1)) + p22r = projector(fg, (i2, j2, 2), (i1, j1, 2)) + + p1r, (p11r, p21r) = fuse_projectors((p11r, p21r)) + p2r, (p12r, p22r) = fuse_projectors((p12r, p22r)) + + pl = outer_projector(p1l, p2l) + pr = outer_projector(p1r, p2r) + + e11 = interaction_energy(fg, (i1, j1, 1), (i2, j2, 1)) + e12 = interaction_energy(fg, (i1, j1, 1), (i2, j2, 2)) + e21 = interaction_energy(fg, (i1, j1, 2), (i2, j2, 1)) + e22 = interaction_energy(fg, (i1, j1, 2), (i2, j2, 2)) + + e11 = e11[p11l, p11r] + e21 = e21[p21l, p21r] + e12 = e12[p12l, p12r] + e22 = e22[p22l, p22r] + + MergedEnergy(e11, e12, e21, e22), pl, pr +end + +function local_energy(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}) where {S, T} + has_vertex(fg, v) ? get_prop(fg, v, :spectrum).energies : zeros(1) +end + +function interaction_energy(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} + if has_edge(fg, w, v) + get_prop(fg, w, v, :en)' + elseif has_edge(fg, v, w) + get_prop(fg, v, w, :en) + else + zeros(1, 1) + end +end + +function projector(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} + if has_edge(fg, w, v) + p = get_prop(fg, w, v, :pr) + elseif has_edge(fg, v, w) + p = get_prop(fg, v, w, :pl) + else + p = ones(Int, v ∈ vertices(fg) ? length(get_prop(fg, v, :spectrum).energies) : 1) + end +end + +function fuse_projectors( + projectors::NTuple{N, K} + ) where {N, K} + fused, transitions_matrix = rank_reveal(hcat(projectors...), :PE) + transitions = Tuple(Array(t) for t ∈ eachcol(transitions_matrix)) + fused, transitions +end + +function outer_projector(p1::Array{T, 1}, p2::Array{T, 1}) where T <: Number + reshape(reshape(p1, :, 1) .+ maximum(p1) .* reshape(p2 .- 1, 1, :), :) +end + diff --git a/src/factor.jl b/src/factor.jl index de8bdd8..b962b11 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -5,15 +5,10 @@ export split_into_clusters, decode_factor_graph_state, energy, + energy_2site, cluster_size, - truncate_factor_graph_2site_energy, - truncate_factor_graph_1site_BP, - truncate_factor_graph_2site_BP, - belief_propagation, - belief_propagation_old, - exact_cond_prob, - beliefs_2site, - factor_graph_2site + truncate_factor_graph, + exact_cond_prob """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ @@ -141,134 +136,9 @@ function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_fg end -function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} - length(get_prop(factor_graph, vertex, :spectrum).energies) -end - - -function truncate_factor_graph_2site_energy(fg::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 - states = Dict() - for node in vertices(fg) - if node in keys(states) continue end - i, j, _ = node - E1 = copy(get_prop(fg, (i, j, 1), :spectrum).energies) - E2 = copy(get_prop(fg, (i, j, 2), :spectrum).energies) - E = energy_2site(fg, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) - sx, sy = size(E) - E = reshape(E, sx * sy) - ind1, ind2 = select_numstate_best(E, sx, num_states) - push!(states, (i, j, 1) => ind1) - push!(states, (i, j, 2) => ind2) - end - truncate_factor_graph(fg, states) -end - -function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 - new_fg = factor_graph_2site(fg, beta) - beliefs = belief_propagation(new_fg, beta; tol, iter) - states = Dict() - for node in vertices(fg) - if node in keys(states) continue end - i, j, _ = node - sx = length(get_prop(fg, (i, j, 1), :spectrum).energies) - E = beliefs[(i,j)] - ind1, ind2 = select_numstate_best(E, sx, num_states) - push!(states, (i, j, 1) => ind1) - push!(states, (i, j, 2) => ind2) - end - truncate_factor_graph(fg, states) -end - -# truncate based on energy in two nodes of factor graph; resulting states are a product of states in two nodes, so we have to fine-tune to end up with expected number of states -function select_numstate_best(E, sx, num_states) - - low, high = 1, min(num_states, length(E)) - - while true - guess = div(low + high, 2) - ind = partialsortperm(E, 1:guess) - ind1 = mod.(ind .- 1, sx) .+ 1 - ind2 = div.(ind .- 1, sx) .+ 1 - ind1 = sort([Set(ind1)...]) - ind2 = sort([Set(ind2)...]) - if high - low <= 1 - return ind1, ind2 - end - if length(ind1) * length(ind2) > num_states - high = guess - else - low = guess - end - end -end - -function get_neighbors(graph::LabelledGraph{S, T}, vertex::NTuple) where {S, T} - neighbors = [] - for edge in edges(graph) - src_node, dst_node = src(edge), dst(edge) - if src_node == vertex - push!(neighbors, dst_node) - elseif dst_node == vertex - push!(neighbors, src_node) - end - end - return neighbors -end - -# Works for Pegasus and Zephyr -function truncate_factor_graph(fg::LabelledGraph{S, T}, states::Dict) where {S, T} - - new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) - - for v ∈ vertices(new_fg) - cl = get_prop(fg, v, :cluster) - sp = get_prop(fg, v, :spectrum) - sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) - set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) - end - - for e ∈ edges(fg) - v, w = src(e), dst(e) - add_edge!(new_fg, v, w) - outer_edges = get_prop(fg, v, w, :outer_edges) - pl = get_prop(fg, v, w, :pl) - pr = get_prop(fg, v, w, :pr) - en = get_prop(fg, v, w, :en) - pl = pl[states[v]] - pr = pr[states[w]] - pl_transition, pl_unique = rank_reveal(pl, :PE) - pr_transition, pr_unique = rank_reveal(pr, :PE) - en = en[pl_unique, pr_unique] - - set_props!( - new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) - ) - end - new_fg -end - -function truncate_factor_graph_1site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} - states = Dict() - beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) - for node in vertices(fg) - indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node]))) - push!(states, node => indices) - end - truncate_factor_graph(fg, states) -end - - -function beliefs_2site(fg::LabelledGraph{S, T}, i::Int, j::Int, messages_av::Dict, beta::Real) where {S, T} - temp = energy_2site(fg, i, j) - temp = exp.(-beta*temp) - if ((i, j, 1), (i, j, 2)) in keys(messages_av) - temp = temp .* reshape(messages_av[(i, j, 1), (i, j, 2)], :, 1) - temp = temp .*reshape(messages_av[(i, j, 2), (i, j, 1)], 1, :) - end - temp ./= sum(temp) -end function energy_2site(fg::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} + # matrix of interaction energies between two nodes if has_edge(fg, (i, j, 1), (i, j, 2)) en12 = copy(get_prop(fg, (i, j, 1), (i, j, 2), :en)) pl = copy(get_prop(fg, (i, j, 1), (i, j, 2), :pl)) @@ -285,71 +155,8 @@ function energy_2site(fg::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} int_eng end - -function belief_propagation_old(fg, beta; tol=1e-6, iter=1, output_message=false) - messages_va = Dict() - messages_av = Dict() - beliefs = Dict() - - # Initialize messages with uniform probabilities - for v in vertices(fg) - ns = length(get_prop(fg, v, :spectrum).states) - push!(beliefs, v => ones(ns)./ns) - for neighbor in get_neighbors(fg, v) - push!(messages_va, (v, neighbor) => ones(ns)./ns) - push!(messages_av, (neighbor, v) => ones(ns)./ns) - end - end - - # Perform message passing until convergence - converged = false - iteration = 0 - while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold - iteration += 1 - old_beliefs = deepcopy(beliefs) - for v in vertices(fg) - for neighbor in get_neighbors(fg, v) - #update messages from vertex to edge - messages_va[v, neighbor] = beliefs[v]./messages_av[neighbor, v] - messages_va[v, neighbor] ./= sum(messages_va[v, neighbor]) - end - end - for v in vertices(fg) - for neighbor in get_neighbors(fg, v) - #update messages from edge to vertex - if has_edge(fg, v, neighbor) - E_bond = get_prop(fg, v, neighbor, :en) - pl, pr = get_prop(fg, v, neighbor, :pl), get_prop(fg, v, neighbor, :pr) - elseif has_edge(fg, neighbor, v) - E_bond = get_prop(fg, neighbor, v, :en)' - pl, pr = get_prop(fg, neighbor, v, :pr), get_prop(fg, neighbor, v, :pl) - end - temp = zeros(maximum(pr)) - for (i, r) in enumerate(pr) - temp[r] += messages_va[neighbor, v][i] - end - temp = exp.(-beta * E_bond) * temp - messages_av[neighbor, v] = temp[pl] - messages_av[neighbor, v] ./= sum(messages_av[neighbor, v]) - end - end - - for v in vertices(fg) - E_local = get_prop(fg, v, :spectrum).energies - beliefs[v] = exp.(-E_local * beta) - for neighbor in get_neighbors(fg, v) - #update beliefs - beliefs[v] .*= messages_av[neighbor, v] - end - # Normalize the beliefs - beliefs[v] ./= sum(beliefs[v]) - end - - # Check convergence - converged = all([all(abs.(old_beliefs[v] .- beliefs[v]) .< tol) for v in keys(beliefs)]) - end - - output_message ? (beliefs, messages_av) : beliefs +function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} + length(get_prop(factor_graph, vertex, :spectrum).energies) end function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors @@ -362,245 +169,33 @@ function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state:: sum(prob[findall([all(s[k] == v for (k, v) ∈ target_state) for s ∈ states])]) end - function belief_propagation(fg, beta; tol=1e-6, iter=1) - messages_va = Dict() - messages_av = Dict() - beliefs = Dict() - - # Initialize messages with uniform probabilities - for v in vertices(fg) - ns = length(get_prop(fg, v, :spectrum).energies) - push!(beliefs, v => ones(ns)./ns) - for neighbor in get_neighbors(fg, v) - pr = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :pr) : get_prop(fg, neighbor, v, :pl) - pl = has_edge(fg, neighbor, v) ? get_prop(fg, neighbor, v, :pr) : get_prop(fg, v, neighbor, :pl) - temp = zeros(maximum(pr)) - for (i, r) in enumerate(pr) - temp[r] += 1 - end - push!(messages_va, (v, neighbor) => temp ./ sum(temp)) - push!(messages_av, (neighbor, v) => ones(maximum(pl))) - end - end - - # Perform message passing until convergence - converged = false - iteration = 0 - while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold - iteration += 1 - old_beliefs = deepcopy(beliefs) - for v in vertices(fg) - for neighbor in get_neighbors(fg, v) - #update messages from vertex to edge - E_local = get_prop(fg, v, :spectrum).energies - E_local = E_local .- minimum(E_local) - messages_va[v, neighbor] = exp.(-E_local * beta) - for n in get_neighbors(fg, v) - if n != neighbor - pl = has_edge(fg, n, v) ? get_prop(fg, n, v, :pr) : get_prop(fg, v, n, :pl) - messages_va[v, neighbor] .*= messages_av[n, v][pl] - end - end - messages_va[v, neighbor] ./= sum(messages_va[v, neighbor]) - pr = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :pl) : get_prop(fg, neighbor, v, :pr) - temp = zeros(maximum(pr)) - for (i, r) in enumerate(pr) - temp[r] += messages_va[v, neighbor][i] - end - messages_va[v, neighbor] = temp - end - end - for v in vertices(fg) - for neighbor in get_neighbors(fg, v) - #update messages from edge to verte - # messages_av[neighbor, v] = exp.(-beta * E_bond) * messages_va[neighbor, v] - E_bond = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :en) : get_prop(fg, neighbor, v, :en)' - messages_av[neighbor, v] = update_message(messages_va[neighbor, v], E_bond, beta) - end - end - - for v in vertices(fg) - E_local = get_prop(fg, v, :spectrum).energies - beliefs[v] = exp.(-E_local * beta) - for neighbor in get_neighbors(fg, v) - #update beliefs - pl = has_edge(fg, neighbor, v) ? get_prop(fg, neighbor, v, :pr) : get_prop(fg, v, neighbor, :pl) - beliefs[v] .*= messages_av[neighbor, v][pl] - end - # Normalize the beliefs - beliefs[v] = -log.(beliefs[v])./beta - beliefs[v] = beliefs[v] .- minimum(beliefs[v]) - end - - # Check convergence - converged = all([all(abs.(old_beliefs[v] .- beliefs[v]) .< tol) for v in keys(beliefs)]) - end - - beliefs -end - -struct Energy{T <: Real} - e11::AbstractMatrix{T} - e12::AbstractMatrix{T} - e21::AbstractMatrix{T} - e22::AbstractMatrix{T} -end - -Base.adjoint(s::Energy) = Energy(s.e11', s.e21', s.e12', s.e22') - -function update_message(message::Vector, E_bond::Matrix, beta::Real) - E_bond = E_bond .- minimum(E_bond) - exp.(-beta * E_bond) * message -end - -# function update_message(message::Vector, E_bond::Energy, beta::Real) -# e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 -# @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] -# exp.(-beta * E) * message -# end - -function update_message(message::Vector, E_bond::Energy, beta::Real) - e11, e12, e21, e22 = E_bond.e11', E_bond.e21', E_bond.e12', E_bond.e22' - sbt = length(message) - sl1, sl2, sr1, sr2 = size(e11, 1), size(e22, 1), size(e11, 2), size(e22, 2) - sinter = sbt * max(sl1 * sl2 * min(sr1, sr2), sr1 * sr2 * min(sl1, sl2)) - if sl1 * sl2 * sr1 * sr2 < sinter - e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 - @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] - return exp.(-beta * E) * message - elseif sr1 <= sr2 && sl1 <= sl2 - message = message' - message = message .* (exp.(-beta * e21))' - message = message * (exp.(-beta * e22)) - message .*= (exp.(-beta * e11)) - message .*= (exp.(-beta * e12)) - elseif sr1 <= sr2 && sl2 <= sl1 - message = message' - message = message .* (exp.(-beta * e11))' - message = message * (exp.(-beta * e12)) - message .*= (exp.(-beta * e21)) - message .*= (exp.(-beta * e22)) - elseif sr2 <= sr1 && sl1 <= sl2 - message = message' - message = message .* (exp.(-beta * e22))' - message = message * (exp.(-beta * e21)) - message .*= (exp.(-beta * e11)) - message .*= (exp.(-beta * e12)) - else # sr2 <= sr1 && sl2 <= sl1 - message = message' - message = message .* (exp.(-beta * e12))' - message = message * (exp.(-beta * e11)) - message .*= (exp.(-beta * e21)) - message .*= (exp.(-beta * e22)) - end - reshape(message, sr1 * sr2) -end - -function unify_vertices(vertices::Vector{Tuple{Int64, Int64, Int64}}) - unified_vertices = Vector{Tuple{Int64, Int64}}() - for vertex in vertices - push!(unified_vertices, vertex[1:2]) - end - return unique(unified_vertices) -end +function truncate_factor_graph(fg::LabelledGraph{S, T}, states::Dict) where {S, T} -function factor_graph_2site(fg::LabelledGraph{S, T}, beta::Real) where {S, T} - new_fg = LabelledGraph{MetaDiGraph}(unify_vertices(vertices(fg))) + new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) - for v in vertices(fg) - i, j, _ = v - E1 = copy(get_prop(fg, (i, j, 1), :spectrum).energies) - E2 = copy(get_prop(fg, (i, j, 2), :spectrum).energies) - E = energy_2site(fg, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) - sp = Spectrum(reshape(E, :), []) - set_props!(new_fg, (i, j), Dict(:spectrum => sp)) + for v ∈ vertices(new_fg) + cl = get_prop(fg, v, :cluster) + sp = get_prop(fg, v, :spectrum) + sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) + set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) end - edge_states = Set() for e ∈ edges(fg) - if e in edge_states continue end v, w = src(e), dst(e) - v1, v2, _ = v - w1, w2, _ = w - if (v1, v2) != (w1, w2) - add_edge!(new_fg, (v1, v2), (w1, w2)) - - E, pl, pr = merge_vertices(fg, beta, v, w) - push!(edge_states, sort([(v1, v2), (w1, w2)])) + add_edge!(new_fg, v, w) + outer_edges = get_prop(fg, v, w, :outer_edges) + pl = get_prop(fg, v, w, :pl) + pr = get_prop(fg, v, w, :pr) + en = get_prop(fg, v, w, :en) + pl = pl[states[v]] + pr = pr[states[w]] + pl_transition, pl_unique = rank_reveal(pl, :PE) + pr_transition, pr_unique = rank_reveal(pr, :PE) + en = en[pl_unique, pr_unique] - set_props!( - new_fg, (v1, v2), (w1, w2), Dict(:pl => pl, :en => E, :pr => pr) + set_props!( + new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) ) - end end new_fg end - -function merge_vertices(fg::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int64}, node2::NTuple{3, Int64} - ) where {S, T} - i1, j1, k1 = node1 - i2, j2, k2 = node2 - - p21l = projector(fg, (i1, j1, 2), (i2, j2, 1)) - p22l = projector(fg, (i1, j1, 2), (i2, j2, 2)) - p12l = projector(fg, (i1, j1, 1), (i2, j2, 2)) - p11l = projector(fg, (i1, j1, 1), (i2, j2, 1)) - - p1l, (p11l, p12l) = fuse_projectors((p11l, p12l)) - p2l, (p21l, p22l) = fuse_projectors((p21l, p22l)) - - p11r = projector(fg, (i2, j2, 1), (i1, j1, 1)) - p21r = projector(fg, (i2, j2, 1), (i1, j1, 2)) - p12r = projector(fg, (i2, j2, 2), (i1, j1, 1)) - p22r = projector(fg, (i2, j2, 2), (i1, j1, 2)) - - p1r, (p11r, p21r) = fuse_projectors((p11r, p21r)) - p2r, (p12r, p22r) = fuse_projectors((p12r, p22r)) - - pl = outer_projector(p1l, p2l) - pr = outer_projector(p1r, p2r) - - e11 = interaction_energy(fg, (i1, j1, 1), (i2, j2, 1)) - e12 = interaction_energy(fg, (i1, j1, 1), (i2, j2, 2)) - e21 = interaction_energy(fg, (i1, j1, 2), (i2, j2, 1)) - e22 = interaction_energy(fg, (i1, j1, 2), (i2, j2, 2)) - - e11 = e11[p11l, p11r] - e21 = e21[p21l, p21r] - e12 = e12[p12l, p12r] - e22 = e22[p22l, p22r] - - Energy(e11, e12, e21, e22), pl, pr -end - -function interaction_energy(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} - if has_edge(fg, w, v) - get_prop(fg, w, v, :en)' - elseif has_edge(fg, v, w) - get_prop(fg, v, w, :en) - else - zeros(1, 1) - end -end - -function projector(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} - if has_edge(fg, w, v) - p = get_prop(fg, w, v, :pr) - elseif has_edge(fg, v, w) - p = get_prop(fg, v, w, :pl) - else - p = ones(Int, v ∈ vertices(fg) ? length(get_prop(fg, v, :spectrum).energies) : 1) - end -end - -function fuse_projectors( - projectors::NTuple{N, K} - ) where {N, K} - fused, transitions_matrix = rank_reveal(hcat(projectors...), :PE) - transitions = Tuple(Array(t) for t ∈ eachcol(transitions_matrix)) - fused, transitions -end - -function outer_projector(p1::Array{T, 1}, p2::Array{T, 1}) where T <: Number - reshape(reshape(p1, :, 1) .+ maximum(p1) .* reshape(p2 .- 1, 1, :), :) -end \ No newline at end of file diff --git a/src/truncate.jl b/src/truncate.jl new file mode 100644 index 0000000..f561762 --- /dev/null +++ b/src/truncate.jl @@ -0,0 +1,72 @@ +export + truncate_factor_graph_2site_energy, + truncate_factor_graph_1site_BP, + truncate_factor_graph_2site_BP + + +function truncate_factor_graph_1site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-10, iter=1) where {S, T} + states = Dict() + beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) + for node in vertices(fg) + indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node]))) + push!(states, node => indices) + end + truncate_factor_graph(fg, states) +end + +function truncate_factor_graph_2site_energy(fg::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 + states = Dict() + for node in vertices(fg) + if node in keys(states) continue end + i, j, _ = node + E1 = copy(get_prop(fg, (i, j, 1), :spectrum).energies) + E2 = copy(get_prop(fg, (i, j, 2), :spectrum).energies) + E = energy_2site(fg, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) + sx, sy = size(E) + E = reshape(E, sx * sy) + ind1, ind2 = select_numstate_best(E, sx, num_states) + push!(states, (i, j, 1) => ind1) + push!(states, (i, j, 2) => ind2) + end + truncate_factor_graph(fg, states) +end + +function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 + new_fg = factor_graph_2site(fg, beta) + beliefs = belief_propagation(new_fg, beta; tol, iter) + states = Dict() + for node in vertices(fg) + if node in keys(states) continue end + i, j, _ = node + sx = has_vertex(fg, (i, j, 1)) ? length(get_prop(fg, (i, j, 1), :spectrum).energies) : 1 + E = beliefs[(i, j)] + ind1, ind2 = select_numstate_best(E, sx, num_states) + push!(states, (i, j, 1) => ind1) + push!(states, (i, j, 2) => ind2) + end + truncate_factor_graph(fg, states) +end + +function select_numstate_best(E, sx, num_states) + # truncate based on energy in two nodes of factor graph; + # resulting states are a product of states in two nodes, so we have to fine-tune to end up with expected number of states + + low, high = 1, min(num_states, length(E)) + + while true + guess = div(low + high, 2) + ind = partialsortperm(E, 1:guess) + ind1 = mod.(ind .- 1, sx) .+ 1 + ind2 = div.(ind .- 1, sx) .+ 1 + ind1 = sort([Set(ind1)...]) + ind2 = sort([Set(ind2)...]) + if high - low <= 1 + return ind1, ind2 + end + if length(ind1) * length(ind2) > num_states + high = guess + else + low = guess + end + end +end diff --git a/test/bp_2site.jl b/test/bp_2site.jl index 0ef7cd1..6aedd34 100644 --- a/test/bp_2site.jl +++ b/test/bp_2site.jl @@ -71,11 +71,11 @@ end """ Instance below looks like this: -1 -- 2 -- 3 - | - 4 - | - 5 +12 -- 345 -- 6 + | + 789 + | + 10 """ function create_larger_example_factor_graph_tree_2site_pathological() @@ -175,7 +175,7 @@ end @test get_prop(new_fg1, src(e), dst(e), :pr) == get_prop(fg1, src(e), dst(e), :pr) end - beliefs = belief_propagation(new_fg1, beta; iter=iter, tol=tol, output_message=false) + beliefs = belief_propagation(new_fg1, beta; iter=iter, tol=tol) exact_marginal = Dict() for k in keys(beliefs) diff --git a/test/runtests.jl b/test/runtests.jl index 8571b3d..8d0576a 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -27,9 +27,9 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) end my_tests = [ - "ising.jl", - "factor.jl", - "utils.jl", + # "ising.jl", + # "factor.jl", + # "utils.jl", "bp_1site.jl", "bp_2site.jl" ] From de5fa923ad950886066bab1868f079fe299fe277 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 21 Jul 2023 14:11:52 +0200 Subject: [PATCH 154/218] clean bp --- src/bp.jl | 154 ++++++++++++++++++++++------------------------- test/runtests.jl | 10 +-- 2 files changed, 76 insertions(+), 88 deletions(-) diff --git a/src/bp.jl b/src/bp.jl index 8df7450..4192fe5 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -10,15 +10,8 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) # Initialize messages with uniform probabilities for v in vertices(fg) - for neighbor in get_neighbors(fg, v) - pr = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :pr) : get_prop(fg, neighbor, v, :pl) - pl = has_edge(fg, neighbor, v) ? get_prop(fg, neighbor, v, :pr) : get_prop(fg, v, neighbor, :pl) - temp = zeros(maximum(pr)) - for (i, r) in enumerate(pr) - temp[r] += 1 - end - push!(messages_ve, (v, neighbor) => temp ./ sum(temp)) - push!(messages_ev, (neighbor, v) => ones(maximum(pl))) + for (n, pv, _) in get_neighbors(fg, v) + push!(messages_ev, (n, v) => ones(maximum(pv))) end end @@ -27,51 +20,43 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) iteration = 0 while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold iteration += 1 - old_messages_ve = deepcopy(messages_ve) + old_messages_ev = deepcopy(messages_ev) for v in vertices(fg) - for neighbor in get_neighbors(fg, v) - #update messages from vertex to edge + #update messages from vertex to edge + for (n1, pv1, _) ∈ get_neighbors(fg, v) E_local = get_prop(fg, v, :spectrum).energies - E_local = E_local .- minimum(E_local) - messages_ve[v, neighbor] = exp.(-E_local * beta) - for n in get_neighbors(fg, v) - if n != neighbor - pl = has_edge(fg, n, v) ? get_prop(fg, n, v, :pr) : get_prop(fg, v, n, :pl) - messages_ve[v, neighbor] .*= messages_ev[n, v][pl] - end + messages_ve[v, n1] = exp.(-(E_local .- minimum(E_local)) * beta) + for (n2, pv2, _) in get_neighbors(fg, v) + if n1 == n2 continue end + messages_ve[v, n1] .*= messages_ev[n2, v][pv2] end - messages_ve[v, neighbor] ./= sum(messages_ve[v, neighbor]) - pr = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :pl) : get_prop(fg, neighbor, v, :pr) - temp = zeros(maximum(pr)) - for (i, r) in enumerate(pr) - temp[r] += messages_ve[v, neighbor][i] + messages_ve[v, n1] ./= sum(messages_ve[v, n1]) + temp = zeros(maximum(pv1)) + for (i, r) in enumerate(pv1) + temp[r] += messages_ve[v, n1][i] end - messages_ve[v, neighbor] = temp + messages_ve[v, n1] = temp end end + + #update messages from edge to verte for v in vertices(fg) - for neighbor in get_neighbors(fg, v) - #update messages from edge to verte - # messages_ev[neighbor, v] = exp.(-beta * E_bond) * messages_ve[neighbor, v] - E_bond = has_edge(fg, v, neighbor) ? get_prop(fg, v, neighbor, :en) : get_prop(fg, neighbor, v, :en)' - messages_ev[neighbor, v] = update_message(messages_ve[neighbor, v], E_bond, beta) + for (n, _, en) ∈ get_neighbors(fg, v) + messages_ev[n, v] = update_message(en, messages_ve[n, v], beta) end end # Check convergence - # converged = all([all(abs.(old_messages_ve[v] .- messages_ve[v]) .< tol) for v in keys(messages_ve)]) + converged = all([all(abs.(old_messages_ev[v] .- messages_ev[v]) .< tol) for v in keys(messages_ev)]) end beliefs = Dict() for v in vertices(fg) E_local = get_prop(fg, v, :spectrum).energies beliefs[v] = exp.(-E_local * beta) - for neighbor in get_neighbors(fg, v) - #update beliefs - pl = has_edge(fg, neighbor, v) ? get_prop(fg, neighbor, v, :pr) : get_prop(fg, v, neighbor, :pl) - beliefs[v] .*= messages_ev[neighbor, v][pl] + for (n, pv, _) ∈ get_neighbors(fg, v) + beliefs[v] .*= messages_ev[n, v][pv] end - # Normalize the beliefs beliefs[v] = -log.(beliefs[v])./beta beliefs[v] = beliefs[v] .- minimum(beliefs[v]) end @@ -79,15 +64,18 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) beliefs end - -function get_neighbors(graph::LabelledGraph{S, T}, vertex::NTuple) where {S, T} +function get_neighbors(fg::LabelledGraph{S, T}, vertex::NTuple) where {S, T} neighbors = [] - for edge in edges(graph) + for edge in edges(fg) src_node, dst_node = src(edge), dst(edge) if src_node == vertex - push!(neighbors, dst_node) + en = get_prop(fg, src_node, dst_node, :en) + pv = get_prop(fg, src_node, dst_node, :pl) + push!(neighbors, (dst_node, pv, en)) elseif dst_node == vertex - push!(neighbors, src_node) + en = get_prop(fg, src_node, dst_node, :en)' + pv = get_prop(fg, src_node, dst_node, :pr) + push!(neighbors, (src_node, pv, en)) end end return neighbors @@ -102,51 +90,52 @@ end Base.adjoint(s::MergedEnergy) = MergedEnergy(s.e11', s.e21', s.e12', s.e22') -function update_message(message::Vector, E_bond::AbstractArray, beta::Real) +function update_message( E_bond::AbstractArray, message::Vector, beta::Real) E_bond = E_bond .- minimum(E_bond) exp.(-beta * E_bond) * message end -function update_message(message::Vector, E_bond::MergedEnergy, beta::Real) +function update_message(E_bond::MergedEnergy, message::Vector, beta::Real) # equivalent to - # @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] - # exp.(-beta * E) * message - # but without creating large matrix E if not optimal + e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 + @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] + exp.(-beta * E) * message - e11, e12, e21, e22 = E_bond.e11', E_bond.e21', E_bond.e12', E_bond.e22' - sbt = length(message) - sl1, sl2, sr1, sr2 = size(e11, 1), size(e22, 1), size(e11, 2), size(e22, 2) - sinter = sbt * max(sl1 * sl2 * min(sr1, sr2), sr1 * sr2 * min(sl1, sl2)) - if sl1 * sl2 * sr1 * sr2 < sinter - e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 - @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] - return exp.(-beta * E) * message - elseif sr1 <= sr2 && sl1 <= sl2 - message = message' - message = message .* (exp.(-beta * e21))' - message = message * (exp.(-beta * e22)) - message .*= (exp.(-beta * e11)) - message .*= (exp.(-beta * e12)) - elseif sr1 <= sr2 && sl2 <= sl1 - message = message' - message = message .* (exp.(-beta * e11))' - message = message * (exp.(-beta * e12)) - message .*= (exp.(-beta * e21)) - message .*= (exp.(-beta * e22)) - elseif sr2 <= sr1 && sl1 <= sl2 - message = message' - message = message .* (exp.(-beta * e22))' - message = message * (exp.(-beta * e21)) - message .*= (exp.(-beta * e11)) - message .*= (exp.(-beta * e12)) - else # sr2 <= sr1 && sl2 <= sl1 - message = message' - message = message .* (exp.(-beta * e12))' - message = message * (exp.(-beta * e11)) - message .*= (exp.(-beta * e21)) - message .*= (exp.(-beta * e22)) - end - reshape(message, sr1 * sr2) + # but without creating large matrix E if not optimal + # e11, e12, e21, e22 = E_bond.e11', E_bond.e21', E_bond.e12', E_bond.e22' + # sbt = length(message) + # sl1, sl2, sr1, sr2 = size(e11, 1), size(e22, 1), size(e11, 2), size(e22, 2) + # sinter = sbt * max(sl1 * sl2 * min(sr1, sr2), sr1 * sr2 * min(sl1, sl2)) + # if sl1 * sl2 * sr1 * sr2 < sinter + # e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 + # @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] + # return exp.(-beta * E) * message + # elseif sr1 <= sr2 && sl1 <= sl2 + # message = message' + # message = message .* (exp.(-beta * e21))' + # message = message * (exp.(-beta * e22)) + # message .*= (exp.(-beta * e11)) + # message .*= (exp.(-beta * e12)) + # elseif sr1 <= sr2 && sl2 <= sl1 + # message = message' + # message = message .* (exp.(-beta * e11))' + # message = message * (exp.(-beta * e12)) + # message .*= (exp.(-beta * e21)) + # message .*= (exp.(-beta * e22)) + # elseif sr2 <= sr1 && sl1 <= sl2 + # message = message' + # message = message .* (exp.(-beta * e22))' + # message = message * (exp.(-beta * e21)) + # message .*= (exp.(-beta * e11)) + # message .*= (exp.(-beta * e12)) + # else # sr2 <= sr1 && sl2 <= sl1 + # message = message' + # message = message .* (exp.(-beta * e12))' + # message = message * (exp.(-beta * e11)) + # message .*= (exp.(-beta * e21)) + # message .*= (exp.(-beta * e22)) + # end + # reshape(message, sr1 * sr2) end @@ -187,8 +176,8 @@ end function merge_vertices(fg::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int64}, node2::NTuple{3, Int64} ) where {S, T} - i1, j1, k1 = node1 - i2, j2, k2 = node2 + i1, j1, _ = node1 + i2, j2, _ = node2 p21l = projector(fg, (i1, j1, 2), (i2, j2, 1)) p22l = projector(fg, (i1, j1, 2), (i2, j2, 2)) @@ -257,4 +246,3 @@ end function outer_projector(p1::Array{T, 1}, p2::Array{T, 1}) where T <: Number reshape(reshape(p1, :, 1) .+ maximum(p1) .* reshape(p2 .- 1, 1, :), :) end - diff --git a/test/runtests.jl b/test/runtests.jl index 8d0576a..87da274 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -27,12 +27,12 @@ function _energy(config::Dict, couplings::Dict, cedges::Dict, n::Int) end my_tests = [ - # "ising.jl", - # "factor.jl", - # "utils.jl", + "ising.jl", + "factor.jl", "bp_1site.jl", - "bp_2site.jl" -] + "bp_2site.jl", + "utils.jl" + ] for my_test ∈ my_tests include(my_test) From ed152c8c4884dc04f2aa17e6eb856ee966935166 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 21 Jul 2023 19:28:24 +0200 Subject: [PATCH 155/218] updatemessage --- src/bp.jl | 80 ++++++++++++++++++++++++++++--------------------------- 1 file changed, 41 insertions(+), 39 deletions(-) diff --git a/src/bp.jl b/src/bp.jl index 4192fe5..bbdc2ff 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -96,46 +96,48 @@ function update_message( E_bond::AbstractArray, message::Vector, beta::Real) end function update_message(E_bond::MergedEnergy, message::Vector, beta::Real) - # equivalent to e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 - @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] - exp.(-beta * E) * message - - # but without creating large matrix E if not optimal - # e11, e12, e21, e22 = E_bond.e11', E_bond.e21', E_bond.e12', E_bond.e22' - # sbt = length(message) - # sl1, sl2, sr1, sr2 = size(e11, 1), size(e22, 1), size(e11, 2), size(e22, 2) - # sinter = sbt * max(sl1 * sl2 * min(sr1, sr2), sr1 * sr2 * min(sl1, sl2)) - # if sl1 * sl2 * sr1 * sr2 < sinter - # e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 - # @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] - # return exp.(-beta * E) * message - # elseif sr1 <= sr2 && sl1 <= sl2 - # message = message' - # message = message .* (exp.(-beta * e21))' - # message = message * (exp.(-beta * e22)) - # message .*= (exp.(-beta * e11)) - # message .*= (exp.(-beta * e12)) - # elseif sr1 <= sr2 && sl2 <= sl1 - # message = message' - # message = message .* (exp.(-beta * e11))' - # message = message * (exp.(-beta * e12)) - # message .*= (exp.(-beta * e21)) - # message .*= (exp.(-beta * e22)) - # elseif sr2 <= sr1 && sl1 <= sl2 - # message = message' - # message = message .* (exp.(-beta * e22))' - # message = message * (exp.(-beta * e21)) - # message .*= (exp.(-beta * e11)) - # message .*= (exp.(-beta * e12)) - # else # sr2 <= sr1 && sl2 <= sl1 - # message = message' - # message = message .* (exp.(-beta * e12))' - # message = message * (exp.(-beta * e11)) - # message .*= (exp.(-beta * e21)) - # message .*= (exp.(-beta * e22)) - # end - # reshape(message, sr1 * sr2) + # equivalent to + # @cast E[(l1, l2), (r1, r2)] := e11[l1, r1] + e21[l2, r1] + e12[l1, r2] + e22[l2, r2] + # exp.(-beta * E) * message + + e11 = exp.(-beta .* (e11 .- minimum(e11))) + e12 = exp.(-beta .* (e12 .- minimum(e12))) + e21 = exp.(-beta .* (e21 .- minimum(e21))) + e22 = exp.(-beta .* (e22 .- minimum(e22))) + sl1, sl2, sr1, sr2 = size(e11, 1), size(e21, 1), size(e21, 2), size(e22, 2) + + if sl1 * sl2 * sr1 * sr2 < max(sr1 * sr2 * min(sl1, sl2), sl1 * sl2 * min(sr1, sr2)) + R = reshape(e11, sl1, 1, sr1, 1) .* reshape(e21, 1, sl2, sr1, 1) + R = R .* reshape(e12, sl1, 1, 1, sr2) + R = R .* reshape(e22, 1, sl2, 1, sr2) + R = reshape(R, sl1 * sl2, sr1 * sr2) * message + elseif sl1 <= sl2 && sr1 <= sr2 + R = reshape(e12, sl1, 1, sr2) .* reshape(message, 1, sr1, sr2) + R = reshape(reshape(R, sl1 * sr1, sr2) * e22', sl1, sr1, sl2) # [l1, r1, l2] + R .*= reshape(e11, sl1, sr1, 1) # [l1, r1, l2] .* [l1, r1, :] + R .*= reshape(e21', 1, sr1, sl2) # [l1, r1, l2] .* [:, r1, l2] + R = reshape(sum(R, dims=2), sl1 * sl2) + elseif sl1 <= sl2 && sr2 <= sr1 + R = reshape(e11', sr1, sl1, 1) .* reshape(message, sr1, 1, sr2) + R = reshape(e21 * reshape(R, sr1, sl1 * sr2), sl2, sl1, sr2) + R .*= reshape(e12, 1, sl1, sr2) # [l2, l1, r2] .* [:, l1, r2] + R .*= reshape(e22, sl2, 1, sr2) # [l2, l1, r2] .* [l2, :, r2] + R = reshape(reshape(sum(R, dims=3), sl2, sl1)', sl1 * sl2) + elseif sl2 <= sl1 && sr1 <= sr2 + R = reshape(e22, sl2, 1, sr2) .* reshape(message, 1, sr1, sr2) + R = reshape(reshape(R, sl2 * sr1, sr2) * e12', sl2, sr1, sl1) # [l2, r1, l1] + R .*= reshape(e11', 1, sr1, sl1) # [l2, r1, l1] .* [:, r1, l1] + R .*= reshape(e21, sl2, sr1, 1) # [l2, r1, l1] .* [l2, r1, :] + R = reshape(reshape(sum(R, dims=2), sl2, sl1)', sl1 * sl2) + else # sl2 <= sl1 && sr2 <= sr1 + R = reshape(e21', sr1, sl2, 1) .* reshape(message, sr1, 1, sr2) + R = reshape(e11 * reshape(R, sr1, sl2 * sr2), sl1, sl2, sr2) + R .*= reshape(e12, sl1, 1, sr2) # [l1, l2, r2] .* [l1, :, r2] + R .*= reshape(e22, 1, sl2, sr2) # [l1, l2, r2] .* [:, l2, r2] + R = reshape(sum(R, dims=3), sl1 * sl2) + end + R end From 8aca68e78bb18e54279f98d72b18b3b5a0e0b1ab Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 21 Jul 2023 21:52:11 +0200 Subject: [PATCH 156/218] sparse --- Project.toml | 3 +-- src/SpinGlassNetworks.jl | 2 +- src/bp.jl | 20 ++++++++++++-------- test/runtests.jl | 1 + 4 files changed, 15 insertions(+), 11 deletions(-) diff --git a/Project.toml b/Project.toml index c8d2678..3abd888 100644 --- a/Project.toml +++ b/Project.toml @@ -11,8 +11,7 @@ LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2" MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5" -TensorCast = "02d47bb6-7ce6-556a-be16-bb1710789e2b" -TensorOperations = "6aa20fa7-93e2-5fca-9bc0-fbd0db3c71a2" +SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf" [compat] CSV = "0.8" diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 091ba36..bf4c00e 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -6,7 +6,7 @@ module SpinGlassNetworks using DocStringExtensions using LinearAlgebra, MKL using Base.Cartesian - using TensorOperations, TensorCast + using SparseArrays import Base.Prehashed diff --git a/src/bp.jl b/src/bp.jl index bbdc2ff..27d50fb 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -25,17 +25,13 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) #update messages from vertex to edge for (n1, pv1, _) ∈ get_neighbors(fg, v) E_local = get_prop(fg, v, :spectrum).energies - messages_ve[v, n1] = exp.(-(E_local .- minimum(E_local)) * beta) + temp = exp.(-(E_local .- minimum(E_local)) * beta) for (n2, pv2, _) in get_neighbors(fg, v) if n1 == n2 continue end - messages_ve[v, n1] .*= messages_ev[n2, v][pv2] + temp .*= messages_ev[n2, v][pv2] end - messages_ve[v, n1] ./= sum(messages_ve[v, n1]) - temp = zeros(maximum(pv1)) - for (i, r) in enumerate(pv1) - temp[r] += messages_ve[v, n1][i] - end - messages_ve[v, n1] = temp + temp ./= sum(temp) + messages_ve[v, n1] = SparseCSC(eltype(temp), pv1) * temp end end @@ -248,3 +244,11 @@ end function outer_projector(p1::Array{T, 1}, p2::Array{T, 1}) where T <: Number reshape(reshape(p1, :, 1) .+ maximum(p1) .* reshape(p2 .- 1, 1, :), :) end + +function SparseCSC(::Type{R}, p::Vector{Int64}) where R <: Real + n = length(p) + mp = maximum(p) + cn = collect(1:n) + co = ones(R, n) + sparse(p, cn, co, mp, n) +end \ No newline at end of file diff --git a/test/runtests.jl b/test/runtests.jl index 87da274..22efa5d 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -4,6 +4,7 @@ using LightGraphs using MetaGraphs using Logging using Test +using TensorCast Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) From e5bbe621cddc0c31e61916b76282fc6583d03513 Mon Sep 17 00:00:00 2001 From: marekrams Date: Mon, 24 Jul 2023 12:36:17 +0200 Subject: [PATCH 157/218] bp --- src/bp.jl | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/src/bp.jl b/src/bp.jl index 27d50fb..bdef276 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -23,12 +23,16 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) old_messages_ev = deepcopy(messages_ev) for v in vertices(fg) #update messages from vertex to edge + node_messages = Dict() + for (n1, pv1, _) ∈ get_neighbors(fg, v) + node_messages[n1, v] = messages_ev[n1, v][pv1] + end for (n1, pv1, _) ∈ get_neighbors(fg, v) E_local = get_prop(fg, v, :spectrum).energies temp = exp.(-(E_local .- minimum(E_local)) * beta) for (n2, pv2, _) in get_neighbors(fg, v) if n1 == n2 continue end - temp .*= messages_ev[n2, v][pv2] + temp .*= node_messages[n2, v] # messages_ev[n2, v][pv2] end temp ./= sum(temp) messages_ve[v, n1] = SparseCSC(eltype(temp), pv1) * temp From 3652a90fc363237a389b188949bef6e0f54785e2 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 9 Aug 2023 08:03:23 +0200 Subject: [PATCH 158/218] separate truncation and BP --- src/bp.jl | 2 +- src/truncate.jl | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/src/bp.jl b/src/bp.jl index bdef276..bc7ca72 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -39,7 +39,7 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) end end - #update messages from edge to verte + #update messages from edge to vertex for v in vertices(fg) for (n, _, en) ∈ get_neighbors(fg, v) messages_ev[n, v] = update_message(en, messages_ve[n, v], beta) diff --git a/src/truncate.jl b/src/truncate.jl index f561762..53b715f 100644 --- a/src/truncate.jl +++ b/src/truncate.jl @@ -31,9 +31,9 @@ function truncate_factor_graph_2site_energy(fg::LabelledGraph{S, T}, num_states: truncate_factor_graph(fg, states) end -function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-6, iter=1) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 - new_fg = factor_graph_2site(fg, beta) - beliefs = belief_propagation(new_fg, beta; tol, iter) +function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, beliefs::Dict, num_states::Int; beta=1.0, tol=1e-6) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 + # new_fg = factor_graph_2site(fg, beta) + # beliefs = belief_propagation(new_fg, beta; tol, iter) states = Dict() for node in vertices(fg) if node in keys(states) continue end From e9b2a8f6cfbc99cb702cb36ad1b8434bdf57699c Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 9 Aug 2023 08:27:08 +0200 Subject: [PATCH 159/218] rm tol --- src/truncate.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/truncate.jl b/src/truncate.jl index 53b715f..e385fa3 100644 --- a/src/truncate.jl +++ b/src/truncate.jl @@ -31,7 +31,7 @@ function truncate_factor_graph_2site_energy(fg::LabelledGraph{S, T}, num_states: truncate_factor_graph(fg, states) end -function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, beliefs::Dict, num_states::Int; beta=1.0, tol=1e-6) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 +function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, beliefs::Dict, num_states::Int; beta=1.0) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 # new_fg = factor_graph_2site(fg, beta) # beliefs = belief_propagation(new_fg, beta; tol, iter) states = Dict() From e67c16404142a58c15eb9043d9469b2ba1b12d69 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 16 Aug 2023 12:18:55 +0200 Subject: [PATCH 160/218] truncate fg for zephyr --- src/factor.jl | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/src/factor.jl b/src/factor.jl index b962b11..b85203b 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -176,7 +176,11 @@ function truncate_factor_graph(fg::LabelledGraph{S, T}, states::Dict) where {S, for v ∈ vertices(new_fg) cl = get_prop(fg, v, :cluster) sp = get_prop(fg, v, :spectrum) - sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) + if sp.states == Vector{Int64}[] + sp = Spectrum(sp.energies[states[v]], sp.states) + else + sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) + end set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) end From 42fe63041514fe881809ab6de3a0c328ce788431 Mon Sep 17 00:00:00 2001 From: marekrams Date: Fri, 18 Aug 2023 12:24:27 +0200 Subject: [PATCH 161/218] comment projectors --- src/idea_projectors.jl | 90 +++++++++++++++++++++--------------------- 1 file changed, 45 insertions(+), 45 deletions(-) diff --git a/src/idea_projectors.jl b/src/idea_projectors.jl index a080c4f..5bcb027 100644 --- a/src/idea_projectors.jl +++ b/src/idea_projectors.jl @@ -1,46 +1,46 @@ - -export - PoolOfProjectors - -const Proj{T} = Union{Vector{T}, CuArray{T, 1}} - -struct PoolOfProjectors{T} - data::Dict{Symbol, Dict{Int, Proj{T}}} - default_device::Symbol - - PoolOfProjectors(data:::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(data, :CPU) -end - -Base.eltype(lp::PoolOfProjectors{T}) where T = T -Base.length(lp::PoolOfProjectors, index::Int) = length(lp.data[lp.default_device][index]) -Base.empty(lp::PoolOfProjectors, device::Symbol) = empty!(lp.data[device]) - -# TODO This is version for only one GPU -function get_projector!(lp::PoolOfProjectors, index::Int, device::Symbol) - if device ∉ lp.data - push!(lp.data[device], index => CuArray(lp.data[default_device][index])) - end - lp.data[device][index] -end - -#= -buf_a = Mem.alloc(Mem.Unified, sizeof(a)) -d_a = unsafe_wrap(CuArray{Float32,3}, convert(CuPtr{Float32}, buf_a), dims) -finalizer(d_a) do _ - Mem.free(buf_a) -end -copyto!(d_a, a) -=# - -#= -function add_projector!(lp::PoolOfProjectors, p::Proj) - if p in values(lp.data) - key = key of p_in_lp.data - else - key = generate_new_key - push!(lp.data, key => p) - end - key -end -=# +# currently moved to SpinGlassTensors +# export +# PoolOfProjectors; + +# const Proj{T} = Union{Vector{T}, CuArray{T, 1}} + +# struct PoolOfProjectors{T} +# data::Dict{Symbol, Dict{Int, Proj{T}}} +# default_device::Symbol + +# PoolOfProjectors(data:::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(data, :CPU) +# end + +# Base.eltype(lp::PoolOfProjectors{T}) where T = T +# Base.length(lp::PoolOfProjectors, index::Int) = length(lp.data[lp.default_device][index]) +# Base.empty(lp::PoolOfProjectors, device::Symbol) = empty!(lp.data[device]) + +# # TODO This is version for only one GPU +# function get_projector!(lp::PoolOfProjectors, index::Int, device::Symbol) +# if device ∉ lp.data +# push!(lp.data[device], index => CuArray(lp.data[default_device][index])) +# end +# lp.data[device][index] +# end + +# #= +# buf_a = Mem.alloc(Mem.Unified, sizeof(a)) +# d_a = unsafe_wrap(CuArray{Float32,3}, convert(CuPtr{Float32}, buf_a), dims) +# finalizer(d_a) do _ +# Mem.free(buf_a) +# end +# copyto!(d_a, a) +# =# + +# #= +# function add_projector!(lp::PoolOfProjectors, p::Proj) +# if p in values(lp.data) +# key = key of p_in_lp.data +# else +# key = generate_new_key +# push!(lp.data, key => p) +# end +# key +# end +# =# From 1982ba18f3686df9ee4b87157683688dc8b5b4e2 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 23 Aug 2023 09:57:31 +0200 Subject: [PATCH 162/218] states_int in Spectrum --- src/spectrum.jl | 21 ++++++++++++++++++--- 1 file changed, 18 insertions(+), 3 deletions(-) diff --git a/src/spectrum.jl b/src/spectrum.jl index b06d520..0a5af0b 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -7,7 +7,8 @@ export Spectrum, idx, local_basis, - energy + energy, + matrix_to_integers @inline idx(σ::Int) = (σ == -1) ? 1 : σ + 1 @inline local_basis(d::Int) = union(-1, 1:d-1) @@ -17,6 +18,20 @@ const State = Vector{Int} struct Spectrum energies::Vector{<:Real} states::AbstractArray{State} + states_int::Vector{Int} + function Spectrum(energies, states, states_int) + new(energies, states, states_int) + end + function Spectrum(energies, states) + states_int = matrix_to_integers(states) + new(energies, states, states_int) + end +end + +function matrix_to_integers(matrix::Vector{Vector{Int}}) + nrows = length(matrix[1]) + multipliers = 2 .^ collect(0:nrows-1) + div.((hcat(matrix...)' .+ 1) , 2) * multipliers end function energy(σ::AbstractArray{State}, ig::IsingGraph) @@ -53,7 +68,7 @@ end function brute_force(ig::IsingGraph, ::Val{:CPU}; num_states::Int=1) L = nv(ig) - if L == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end + if L == 0 return Spectrum(zeros(1), Vector{Int}[], zeros(Int, 1)) end sp = Spectrum(ig) num_states = min(num_states, prod(rank_vec(ig))) idx = partialsortperm(vec(sp.energies), 1:num_states) @@ -62,7 +77,7 @@ end #TODO: to be removed function full_spectrum(ig::IsingGraph; num_states::Int=1) - if nv(ig) == 0 return Spectrum(zeros(1), Vector{Vector{Int}}[]) end + if nv(ig) == 0 return Spectrum(zeros(1), Vector{Int}[], zeros(Int, 1)) end ig_rank = rank_vec(ig) num_states = min(num_states, prod(ig_rank)) σ = collect.(all_states(ig_rank)) From 66bbc54819723762a0c8fcfd51e13776c54e2ce0 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 25 Aug 2023 14:29:05 +0200 Subject: [PATCH 163/218] fix the bug in Spectrum, all tests pass --- src/bp.jl | 2 +- test/bp_2site.jl | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/bp.jl b/src/bp.jl index bc7ca72..146ba88 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -153,7 +153,7 @@ function factor_graph_2site(fg::LabelledGraph{S, T}, beta::Real) where {S, T} E1 = local_energy(fg, (i, j, 1)) E2 = local_energy(fg, (i, j, 2)) E = energy_2site(fg, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) - sp = Spectrum(reshape(E, :), []) + sp = Spectrum(reshape(E, :), [], []) set_props!(new_fg, (i, j), Dict(:spectrum => sp)) push!(vertx, (i, j)) end diff --git a/test/bp_2site.jl b/test/bp_2site.jl index 6aedd34..f6f3072 100644 --- a/test/bp_2site.jl +++ b/test/bp_2site.jl @@ -186,7 +186,7 @@ end @test beliefs[v] ≈ exact_marginal[v] end - truncate_factor_graph_2site_BP(fg2, num_states; beta=beta, iter=iter) + truncate_factor_graph_2site_BP(fg2, beliefs, num_states; beta=beta) end end end From f3725a48ff9424c91424876df2caaa4274c9f71a Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 25 Aug 2023 22:59:26 +0200 Subject: [PATCH 164/218] change types in matrix_to_integers --- src/factor.jl | 2 +- src/spectrum.jl | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/factor.jl b/src/factor.jl index b85203b..f13bc39 100644 --- a/src/factor.jl +++ b/src/factor.jl @@ -177,7 +177,7 @@ function truncate_factor_graph(fg::LabelledGraph{S, T}, states::Dict) where {S, cl = get_prop(fg, v, :cluster) sp = get_prop(fg, v, :spectrum) if sp.states == Vector{Int64}[] - sp = Spectrum(sp.energies[states[v]], sp.states) + sp = Spectrum(sp.energies[states[v]], sp.states, []) else sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) end diff --git a/src/spectrum.jl b/src/spectrum.jl index 0a5af0b..3c4041d 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -28,7 +28,7 @@ struct Spectrum end end -function matrix_to_integers(matrix::Vector{Vector{Int}}) +function matrix_to_integers(matrix::Vector{Vector{T}}) where T nrows = length(matrix[1]) multipliers = 2 .^ collect(0:nrows-1) div.((hcat(matrix...)' .+ 1) , 2) * multipliers From a2de583e0168ad16d52e34b6e3c42334dbd70fdb Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Sat, 16 Sep 2023 21:12:39 +0200 Subject: [PATCH 165/218] rename factor_graph to clustered_hamiltonian --- examples/bp.jl | 14 +-- src/SpinGlassNetworks.jl | 2 +- src/bp.jl | 118 +++++++++---------- src/{factor.jl => clustered_hamiltonian.jl} | 116 +++++++++--------- src/truncate.jl | 38 +++--- test/bp_1site.jl | 28 ++--- test/bp_2site.jl | 48 ++++---- test/{factor.jl => clustered_hamiltonian.jl} | 60 +++++----- test/runtests.jl | 2 +- test/spectrum.jl | 8 ++ test/utils.jl | 6 +- 11 files changed, 224 insertions(+), 216 deletions(-) rename src/{factor.jl => clustered_hamiltonian.jl} (55%) rename test/{factor.jl => clustered_hamiltonian.jl} (77%) create mode 100644 test/spectrum.jl diff --git a/examples/bp.jl b/examples/bp.jl index 2ecbad1..029d480 100644 --- a/examples/bp.jl +++ b/examples/bp.jl @@ -13,7 +13,7 @@ Instance below looks like this: | 7 -- 8 -- 9 """ -function create_larger_example_factor_graph_tree() +function create_larger_example_clustered_hamiltonian_tree() instance = Dict( (1, 1) => 0.5, (2, 2) => 0.25, @@ -48,22 +48,22 @@ function create_larger_example_factor_graph_tree() 9 => (3, 3, 1) ) - fg = factor_graph( + cl_h = clustered_hamiltonian( ig, Dict{NTuple{3, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule, ) - ig, fg + ig, cl_h end -ig, fg = create_larger_example_factor_graph_tree() +ig, cl_h = create_larger_example_clustered_hamiltonian_tree() beta = 0.1 iter = 0 -beliefs = belief_propagation(fg, beta; iter=iter) +beliefs = belief_propagation(cl_h, beta; iter=iter) -for v in vertices(fg) - en = get_prop(fg, v, :spectrum).energies +for v in vertices(cl_h) + en = get_prop(cl_h, v, :spectrum).energies println("vertex ", v, " energy = ", en .- minimum(en), " bp = ", beliefs[v]) end diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index bf4c00e..264030c 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -88,7 +88,7 @@ module SpinGlassNetworks include("ising.jl") include("spectrum.jl") include("lattice.jl") - include("factor.jl") + include("clustered_hamiltonian.jl") include("bp.jl") include("truncate.jl") include("utils.jl") diff --git a/src/bp.jl b/src/bp.jl index 146ba88..eb34e9b 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -1,16 +1,16 @@ export belief_propagation, - factor_graph_2site + clustered_hamiltonian_2site -function belief_propagation(fg, beta; tol=1e-6, iter=1) +function belief_propagation(cl_h, beta; tol=1e-6, iter=1) messages_ve = Dict() messages_ev = Dict() # Initialize messages with uniform probabilities - for v in vertices(fg) - for (n, pv, _) in get_neighbors(fg, v) + for v in vertices(cl_h) + for (n, pv, _) in get_neighbors(cl_h, v) push!(messages_ev, (n, v) => ones(maximum(pv))) end end @@ -21,16 +21,16 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) while !converged && iteration < iter # Set an appropriate number of iterations and convergence threshold iteration += 1 old_messages_ev = deepcopy(messages_ev) - for v in vertices(fg) + for v in vertices(cl_h) #update messages from vertex to edge node_messages = Dict() - for (n1, pv1, _) ∈ get_neighbors(fg, v) + for (n1, pv1, _) ∈ get_neighbors(cl_h, v) node_messages[n1, v] = messages_ev[n1, v][pv1] end - for (n1, pv1, _) ∈ get_neighbors(fg, v) - E_local = get_prop(fg, v, :spectrum).energies + for (n1, pv1, _) ∈ get_neighbors(cl_h, v) + E_local = get_prop(cl_h, v, :spectrum).energies temp = exp.(-(E_local .- minimum(E_local)) * beta) - for (n2, pv2, _) in get_neighbors(fg, v) + for (n2, pv2, _) in get_neighbors(cl_h, v) if n1 == n2 continue end temp .*= node_messages[n2, v] # messages_ev[n2, v][pv2] end @@ -40,8 +40,8 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) end #update messages from edge to vertex - for v in vertices(fg) - for (n, _, en) ∈ get_neighbors(fg, v) + for v in vertices(cl_h) + for (n, _, en) ∈ get_neighbors(cl_h, v) messages_ev[n, v] = update_message(en, messages_ve[n, v], beta) end end @@ -51,10 +51,10 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) end beliefs = Dict() - for v in vertices(fg) - E_local = get_prop(fg, v, :spectrum).energies + for v in vertices(cl_h) + E_local = get_prop(cl_h, v, :spectrum).energies beliefs[v] = exp.(-E_local * beta) - for (n, pv, _) ∈ get_neighbors(fg, v) + for (n, pv, _) ∈ get_neighbors(cl_h, v) beliefs[v] .*= messages_ev[n, v][pv] end beliefs[v] = -log.(beliefs[v])./beta @@ -64,17 +64,17 @@ function belief_propagation(fg, beta; tol=1e-6, iter=1) beliefs end -function get_neighbors(fg::LabelledGraph{S, T}, vertex::NTuple) where {S, T} +function get_neighbors(cl_h::LabelledGraph{S, T}, vertex::NTuple) where {S, T} neighbors = [] - for edge in edges(fg) + for edge in edges(cl_h) src_node, dst_node = src(edge), dst(edge) if src_node == vertex - en = get_prop(fg, src_node, dst_node, :en) - pv = get_prop(fg, src_node, dst_node, :pl) + en = get_prop(cl_h, src_node, dst_node, :en) + pv = get_prop(cl_h, src_node, dst_node, :pl) push!(neighbors, (dst_node, pv, en)) elseif dst_node == vertex - en = get_prop(fg, src_node, dst_node, :en)' - pv = get_prop(fg, src_node, dst_node, :pr) + en = get_prop(cl_h, src_node, dst_node, :en)' + pv = get_prop(cl_h, src_node, dst_node, :pr) push!(neighbors, (src_node, pv, en)) end end @@ -141,25 +141,25 @@ function update_message(E_bond::MergedEnergy, message::Vector, beta::Real) end -function factor_graph_2site(fg::LabelledGraph{S, T}, beta::Real) where {S, T} +function clustered_hamiltonian_2site(cl_h::LabelledGraph{S, T}, beta::Real) where {S, T} - unified_vertices = unique([vertex[1:2] for vertex in vertices(fg)]) - new_fg = LabelledGraph{MetaDiGraph}(unified_vertices) + unified_vertices = unique([vertex[1:2] for vertex in vertices(cl_h)]) + new_cl_h = LabelledGraph{MetaDiGraph}(unified_vertices) vertx = Set() - for v in vertices(fg) + for v in vertices(cl_h) i, j, _ = v if (i, j) ∈ vertx continue end - E1 = local_energy(fg, (i, j, 1)) - E2 = local_energy(fg, (i, j, 2)) - E = energy_2site(fg, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) + E1 = local_energy(cl_h, (i, j, 1)) + E2 = local_energy(cl_h, (i, j, 2)) + E = energy_2site(cl_h, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) sp = Spectrum(reshape(E, :), [], []) - set_props!(new_fg, (i, j), Dict(:spectrum => sp)) + set_props!(new_cl_h, (i, j), Dict(:spectrum => sp)) push!(vertx, (i, j)) end edge_states = Set() - for e ∈ edges(fg) + for e ∈ edges(cl_h) if e in edge_states continue end v, w = src(e), dst(e) v1, v2, _ = v @@ -167,32 +167,32 @@ function factor_graph_2site(fg::LabelledGraph{S, T}, beta::Real) where {S, T} if (v1, v2) == (w1, w2) continue end - add_edge!(new_fg, (v1, v2), (w1, w2)) + add_edge!(new_cl_h, (v1, v2), (w1, w2)) - E, pl, pr = merge_vertices(fg, beta, v, w) - set_props!(new_fg, (v1, v2), (w1, w2), Dict(:pl => pl, :en => E, :pr => pr)) + E, pl, pr = merge_vertices(cl_h, beta, v, w) + set_props!(new_cl_h, (v1, v2), (w1, w2), Dict(:pl => pl, :en => E, :pr => pr)) push!(edge_states, sort([(v1, v2), (w1, w2)])) end - new_fg + new_cl_h end -function merge_vertices(fg::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int64}, node2::NTuple{3, Int64} +function merge_vertices(cl_h::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int64}, node2::NTuple{3, Int64} ) where {S, T} i1, j1, _ = node1 i2, j2, _ = node2 - p21l = projector(fg, (i1, j1, 2), (i2, j2, 1)) - p22l = projector(fg, (i1, j1, 2), (i2, j2, 2)) - p12l = projector(fg, (i1, j1, 1), (i2, j2, 2)) - p11l = projector(fg, (i1, j1, 1), (i2, j2, 1)) + p21l = projector(cl_h, (i1, j1, 2), (i2, j2, 1)) + p22l = projector(cl_h, (i1, j1, 2), (i2, j2, 2)) + p12l = projector(cl_h, (i1, j1, 1), (i2, j2, 2)) + p11l = projector(cl_h, (i1, j1, 1), (i2, j2, 1)) p1l, (p11l, p12l) = fuse_projectors((p11l, p12l)) p2l, (p21l, p22l) = fuse_projectors((p21l, p22l)) - p11r = projector(fg, (i2, j2, 1), (i1, j1, 1)) - p21r = projector(fg, (i2, j2, 1), (i1, j1, 2)) - p12r = projector(fg, (i2, j2, 2), (i1, j1, 1)) - p22r = projector(fg, (i2, j2, 2), (i1, j1, 2)) + p11r = projector(cl_h, (i2, j2, 1), (i1, j1, 1)) + p21r = projector(cl_h, (i2, j2, 1), (i1, j1, 2)) + p12r = projector(cl_h, (i2, j2, 2), (i1, j1, 1)) + p22r = projector(cl_h, (i2, j2, 2), (i1, j1, 2)) p1r, (p11r, p21r) = fuse_projectors((p11r, p21r)) p2r, (p12r, p22r) = fuse_projectors((p12r, p22r)) @@ -200,10 +200,10 @@ function merge_vertices(fg::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int6 pl = outer_projector(p1l, p2l) pr = outer_projector(p1r, p2r) - e11 = interaction_energy(fg, (i1, j1, 1), (i2, j2, 1)) - e12 = interaction_energy(fg, (i1, j1, 1), (i2, j2, 2)) - e21 = interaction_energy(fg, (i1, j1, 2), (i2, j2, 1)) - e22 = interaction_energy(fg, (i1, j1, 2), (i2, j2, 2)) + e11 = interaction_energy(cl_h, (i1, j1, 1), (i2, j2, 1)) + e12 = interaction_energy(cl_h, (i1, j1, 1), (i2, j2, 2)) + e21 = interaction_energy(cl_h, (i1, j1, 2), (i2, j2, 1)) + e22 = interaction_energy(cl_h, (i1, j1, 2), (i2, j2, 2)) e11 = e11[p11l, p11r] e21 = e21[p21l, p21r] @@ -213,27 +213,27 @@ function merge_vertices(fg::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int6 MergedEnergy(e11, e12, e21, e22), pl, pr end -function local_energy(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}) where {S, T} - has_vertex(fg, v) ? get_prop(fg, v, :spectrum).energies : zeros(1) +function local_energy(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}) where {S, T} + has_vertex(cl_h, v) ? get_prop(cl_h, v, :spectrum).energies : zeros(1) end -function interaction_energy(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} - if has_edge(fg, w, v) - get_prop(fg, w, v, :en)' - elseif has_edge(fg, v, w) - get_prop(fg, v, w, :en) +function interaction_energy(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} + if has_edge(cl_h, w, v) + get_prop(cl_h, w, v, :en)' + elseif has_edge(cl_h, v, w) + get_prop(cl_h, v, w, :en) else zeros(1, 1) end end -function projector(fg::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} - if has_edge(fg, w, v) - p = get_prop(fg, w, v, :pr) - elseif has_edge(fg, v, w) - p = get_prop(fg, v, w, :pl) +function projector(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} + if has_edge(cl_h, w, v) + p = get_prop(cl_h, w, v, :pr) + elseif has_edge(cl_h, v, w) + p = get_prop(cl_h, v, w, :pl) else - p = ones(Int, v ∈ vertices(fg) ? length(get_prop(fg, v, :spectrum).energies) : 1) + p = ones(Int, v ∈ vertices(cl_h) ? length(get_prop(cl_h, v, :spectrum).energies) : 1) end end diff --git a/src/factor.jl b/src/clustered_hamiltonian.jl similarity index 55% rename from src/factor.jl rename to src/clustered_hamiltonian.jl index f13bc39..533a79e 100644 --- a/src/factor.jl +++ b/src/clustered_hamiltonian.jl @@ -1,13 +1,13 @@ export - factor_graph, + clustered_hamiltonian, rank_reveal, projectors, split_into_clusters, - decode_factor_graph_state, + decode_clustered_hamiltonian_state, energy, energy_2site, cluster_size, - truncate_factor_graph, + truncate_clustered_hamiltonian, exact_cond_prob """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) @@ -22,32 +22,32 @@ end Create factor graph. Factor graph order introduced as a natural order in factor graph coordinates. """ -function factor_graph( +function clustered_hamiltonian( ig::IsingGraph, num_states_cl::Int; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} # e.g. square lattice ) where T ns = Dict(i => num_states_cl for i ∈ Set(values(cluster_assignment_rule))) - factor_graph(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) + clustered_hamiltonian(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end -function factor_graph( +function clustered_hamiltonian( ig::IsingGraph, num_states_cl::Dict{T, Int}; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} ) where T L = maximum(values(cluster_assignment_rule)) - fg = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) + cl_h = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) for (v, cl) ∈ split_into_clusters(ig, cluster_assignment_rule) sp = spectrum(cl, num_states=get(num_states_cl, v, basis_size(cl))) - set_props!(fg, v, Dict(:cluster => cl, :spectrum => sp)) + set_props!(cl_h, v, Dict(:cluster => cl, :spectrum => sp)) end - for (i, v) ∈ enumerate(vertices(fg)), w ∈ vertices(fg)[i+1:end] - cl1, cl2 = get_prop(fg, v, :cluster), get_prop(fg, w, :cluster) + for (i, v) ∈ enumerate(vertices(cl_h)), w ∈ vertices(cl_h)[i+1:end] + cl1, cl2 = get_prop(cl_h, v, :cluster), get_prop(cl_h, w, :cluster) outer_edges, J = inter_cluster_edges(ig, cl1, cl2) if !isempty(outer_edges) @@ -57,26 +57,26 @@ function factor_graph( ind2 = reshape(ind2, length(ind2)) JJ = J[ind1, ind2] - states_v = get_prop(fg, v, :spectrum).states - states_w = get_prop(fg, w, :spectrum).states + states_v = get_prop(cl_h, v, :spectrum).states + states_w = get_prop(cl_h, w, :spectrum).states pl, unique_states_v = rank_reveal([s[ind1] for s ∈ states_v], :PE) pr, unique_states_w = rank_reveal([s[ind2] for s ∈ states_w], :PE) en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) - add_edge!(fg, v, w) + add_edge!(cl_h, v, w) set_props!( - fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) + cl_h, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) ) end end - fg + cl_h end -function factor_graph( +function clustered_hamiltonian( ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T} ) where T - factor_graph( + clustered_hamiltonian( ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule ) end @@ -94,11 +94,11 @@ Returns Dict(vertex of ising graph -> spin value) Assumes that state has the same order as vertices in factor graph! TODO: check the order consistency over external packages. """ -function decode_factor_graph_state(fg, state::Vector{Int}) +function decode_clustered_hamiltonian_state(cl_h, state::Vector{Int}) ret = Dict{Int, Int}() - for (i, vert) ∈ zip(state, vertices(fg)) - spins = get_prop(fg, vert, :cluster).labels - states = get_prop(fg, vert, :spectrum).states + for (i, vert) ∈ zip(state, vertices(cl_h)) + spins = get_prop(cl_h, vert, :cluster).labels + states = get_prop(cl_h, vert, :spectrum).states if length(states) > 0 curr_state = states[i] merge!(ret, Dict(k => v for (k, v) ∈ zip(spins, curr_state))) @@ -125,29 +125,29 @@ function energy(ig::IsingGraph, ig_state::Dict{Int, Int}) en end -function energy(fg::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} - en_fg = 0.0 - for v ∈ vertices(fg) en_fg += get_prop(fg, v, :spectrum).energies[σ[v]] end - for edge ∈ edges(fg) - pl, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :pr) - en = get_prop(fg, edge, :en) - en_fg += en[pl[σ[src(edge)]], pr[σ[dst(edge)]]] +function energy(cl_h::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} + en_cl_h = 0.0 + for v ∈ vertices(cl_h) en_cl_h += get_prop(cl_h, v, :spectrum).energies[σ[v]] end + for edge ∈ edges(cl_h) + pl, pr = get_prop(cl_h, edge, :pl), get_prop(cl_h, edge, :pr) + en = get_prop(cl_h, edge, :en) + en_cl_h += en[pl[σ[src(edge)]], pr[σ[dst(edge)]]] end - en_fg + en_cl_h end -function energy_2site(fg::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} +function energy_2site(cl_h::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} # matrix of interaction energies between two nodes - if has_edge(fg, (i, j, 1), (i, j, 2)) - en12 = copy(get_prop(fg, (i, j, 1), (i, j, 2), :en)) - pl = copy(get_prop(fg, (i, j, 1), (i, j, 2), :pl)) - pr = copy(get_prop(fg, (i, j, 1), (i, j, 2), :pr)) + if has_edge(cl_h, (i, j, 1), (i, j, 2)) + en12 = copy(get_prop(cl_h, (i, j, 1), (i, j, 2), :en)) + pl = copy(get_prop(cl_h, (i, j, 1), (i, j, 2), :pl)) + pr = copy(get_prop(cl_h, (i, j, 1), (i, j, 2), :pr)) int_eng = en12[pl, pr] - elseif has_edge(fg, (i, j, 2), (i, j, 1)) - en21 = copy(get_prop(fg, (i, j, 2), (i, j, 1), :en)) - pl = copy(get_prop(fg, (i, j, 2), (i, j, 1), :pl)) - pr = copy(get_prop(fg, (i, j, 2), (i, j, 1), :pr)) + elseif has_edge(cl_h, (i, j, 2), (i, j, 1)) + en21 = copy(get_prop(cl_h, (i, j, 2), (i, j, 1), :en)) + pl = copy(get_prop(cl_h, (i, j, 2), (i, j, 1), :pl)) + pr = copy(get_prop(cl_h, (i, j, 2), (i, j, 1), :pr)) int_eng = en21[pl, pr]' else int_eng = zeros(1, 1) @@ -155,42 +155,42 @@ function energy_2site(fg::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} int_eng end -function cluster_size(factor_graph::LabelledGraph{S, T}, vertex::T) where {S, T} - length(get_prop(factor_graph, vertex, :spectrum).energies) +function cluster_size(clustered_hamiltonian::LabelledGraph{S, T}, vertex::T) where {S, T} + length(get_prop(clustered_hamiltonian, vertex, :spectrum).energies) end -function exact_cond_prob(factor_graph::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors - ver = vertices(factor_graph) - rank = cluster_size.(Ref(factor_graph), ver) +function exact_cond_prob(clustered_hamiltonian::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors + ver = vertices(clustered_hamiltonian) + rank = cluster_size.(Ref(clustered_hamiltonian), ver) states = [Dict(ver .=> σ) for σ ∈ Iterators.product([1:r for r ∈ rank]...)] - energies = SpinGlassNetworks.energy.(Ref(factor_graph), states) + energies = SpinGlassNetworks.energy.(Ref(clustered_hamiltonian), states) prob = exp.(-beta .* energies) prob ./= sum(prob) sum(prob[findall([all(s[k] == v for (k, v) ∈ target_state) for s ∈ states])]) end -function truncate_factor_graph(fg::LabelledGraph{S, T}, states::Dict) where {S, T} +function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) where {S, T} - new_fg = LabelledGraph{MetaDiGraph}(vertices(fg)) + new_cl_h = LabelledGraph{MetaDiGraph}(vertices(cl_h)) - for v ∈ vertices(new_fg) - cl = get_prop(fg, v, :cluster) - sp = get_prop(fg, v, :spectrum) + for v ∈ vertices(new_cl_h) + cl = get_prop(cl_h, v, :cluster) + sp = get_prop(cl_h, v, :spectrum) if sp.states == Vector{Int64}[] sp = Spectrum(sp.energies[states[v]], sp.states, []) else sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) end - set_props!(new_fg, v, Dict(:cluster => cl, :spectrum => sp)) + set_props!(new_cl_h, v, Dict(:cluster => cl, :spectrum => sp)) end - for e ∈ edges(fg) + for e ∈ edges(cl_h) v, w = src(e), dst(e) - add_edge!(new_fg, v, w) - outer_edges = get_prop(fg, v, w, :outer_edges) - pl = get_prop(fg, v, w, :pl) - pr = get_prop(fg, v, w, :pr) - en = get_prop(fg, v, w, :en) + add_edge!(new_cl_h, v, w) + outer_edges = get_prop(cl_h, v, w, :outer_edges) + pl = get_prop(cl_h, v, w, :pl) + pr = get_prop(cl_h, v, w, :pr) + en = get_prop(cl_h, v, w, :en) pl = pl[states[v]] pr = pr[states[w]] pl_transition, pl_unique = rank_reveal(pl, :PE) @@ -198,8 +198,8 @@ function truncate_factor_graph(fg::LabelledGraph{S, T}, states::Dict) where {S, en = en[pl_unique, pr_unique] set_props!( - new_fg, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) + new_cl_h, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) ) end - new_fg + new_cl_h end diff --git a/src/truncate.jl b/src/truncate.jl index e385fa3..42ecfd2 100644 --- a/src/truncate.jl +++ b/src/truncate.jl @@ -1,50 +1,50 @@ export - truncate_factor_graph_2site_energy, - truncate_factor_graph_1site_BP, - truncate_factor_graph_2site_BP + truncate_clustered_hamiltonian_2site_energy, + truncate_clustered_hamiltonian_1site_BP, + truncate_clustered_hamiltonian_2site_BP -function truncate_factor_graph_1site_BP(fg::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-10, iter=1) where {S, T} +function truncate_clustered_hamiltonian_1site_BP(cl_h::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-10, iter=1) where {S, T} states = Dict() - beliefs = belief_propagation(fg, beta; tol=tol, iter=iter) - for node in vertices(fg) + beliefs = belief_propagation(cl_h, beta; tol=tol, iter=iter) + for node in vertices(cl_h) indices = partialsortperm(beliefs[node], 1:min(num_states, length(beliefs[node]))) push!(states, node => indices) end - truncate_factor_graph(fg, states) + truncate_clustered_hamiltonian(cl_h, states) end -function truncate_factor_graph_2site_energy(fg::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 +function truncate_clustered_hamiltonian_2site_energy(cl_h::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 states = Dict() - for node in vertices(fg) + for node in vertices(cl_h) if node in keys(states) continue end i, j, _ = node - E1 = copy(get_prop(fg, (i, j, 1), :spectrum).energies) - E2 = copy(get_prop(fg, (i, j, 2), :spectrum).energies) - E = energy_2site(fg, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) + E1 = copy(get_prop(cl_h, (i, j, 1), :spectrum).energies) + E2 = copy(get_prop(cl_h, (i, j, 2), :spectrum).energies) + E = energy_2site(cl_h, i, j) .+ reshape(E1, :, 1) .+ reshape(E2, 1, :) sx, sy = size(E) E = reshape(E, sx * sy) ind1, ind2 = select_numstate_best(E, sx, num_states) push!(states, (i, j, 1) => ind1) push!(states, (i, j, 2) => ind2) end - truncate_factor_graph(fg, states) + truncate_clustered_hamiltonian(cl_h, states) end -function truncate_factor_graph_2site_BP(fg::LabelledGraph{S, T}, beliefs::Dict, num_states::Int; beta=1.0) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 - # new_fg = factor_graph_2site(fg, beta) - # beliefs = belief_propagation(new_fg, beta; tol, iter) +function truncate_clustered_hamiltonian_2site_BP(cl_h::LabelledGraph{S, T}, beliefs::Dict, num_states::Int; beta=1.0) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 + # new_cl_h = clustered_hamiltonian_2site(cl_h, beta) + # beliefs = belief_propagation(new_cl_h, beta; tol, iter) states = Dict() - for node in vertices(fg) + for node in vertices(cl_h) if node in keys(states) continue end i, j, _ = node - sx = has_vertex(fg, (i, j, 1)) ? length(get_prop(fg, (i, j, 1), :spectrum).energies) : 1 + sx = has_vertex(cl_h, (i, j, 1)) ? length(get_prop(cl_h, (i, j, 1), :spectrum).energies) : 1 E = beliefs[(i, j)] ind1, ind2 = select_numstate_best(E, sx, num_states) push!(states, (i, j, 1) => ind1) push!(states, (i, j, 2) => ind2) end - truncate_factor_graph(fg, states) + truncate_clustered_hamiltonian(cl_h, states) end function select_numstate_best(E, sx, num_states) diff --git a/test/bp_1site.jl b/test/bp_1site.jl index 756384a..5a679c5 100644 --- a/test/bp_1site.jl +++ b/test/bp_1site.jl @@ -6,7 +6,7 @@ Instance below looks like this: 3 -- 4 """ -function create_larger_example_factor_graph_tree_basic() +function create_larger_example_clustered_hamiltonian_tree_basic() instance = Dict( (1, 1) => -0.50, (2, 2) => 0.25, @@ -26,14 +26,14 @@ function create_larger_example_factor_graph_tree_basic() 4 => (2, 2, 2) ) - fg = factor_graph( + cl_h = clustered_hamiltonian( ig, Dict{NTuple{3, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule, ) - ig, fg + ig, cl_h end """ @@ -45,7 +45,7 @@ Instance below looks like this: | 7 -- 8 -- 9 """ -function create_larger_example_factor_graph_tree() +function create_larger_example_clustered_hamiltonian_tree() instance = Dict( (1, 1) => 0.53, (2, 2) => -0.25, @@ -79,14 +79,14 @@ function create_larger_example_factor_graph_tree() 9 => (3, 3, 1) ) - fg = factor_graph( + cl_h = clustered_hamiltonian( ig, Dict{NTuple{3, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule, ) - ig, fg + ig, cl_h end """ @@ -97,7 +97,7 @@ Instance below looks like this: 7 8 """ -function create_larger_example_factor_graph_tree_pathological() +function create_larger_example_clustered_hamiltonian_tree_pathological() instance = Dict( (1, 1) => 0.52, (2, 2) => 0.25, @@ -130,26 +130,26 @@ function create_larger_example_factor_graph_tree_pathological() 8 => (2, 2) ) - fg = factor_graph( + cl_h = clustered_hamiltonian( ig, Dict{NTuple{2, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule, ) - ig, fg + ig, cl_h end @testset "Belief propagation" begin - for (ig, fg) ∈ [create_larger_example_factor_graph_tree_basic(), - create_larger_example_factor_graph_tree(), - create_larger_example_factor_graph_tree_pathological()] + for (ig, cl_h) ∈ [create_larger_example_clustered_hamiltonian_tree_basic(), + create_larger_example_clustered_hamiltonian_tree(), + create_larger_example_clustered_hamiltonian_tree_pathological()] for beta ∈ [0.5, 1] iter = 16 - beliefs = belief_propagation(fg, beta; iter=iter) + beliefs = belief_propagation(cl_h, beta; iter=iter) exact_marginal = Dict() for k in keys(beliefs) - push!(exact_marginal, k => [exact_cond_prob(fg, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + push!(exact_marginal, k => [exact_cond_prob(cl_h, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) end for v in keys(beliefs) temp = -log.(exact_marginal[v])./beta diff --git a/test/bp_2site.jl b/test/bp_2site.jl index f6f3072..ee4962f 100644 --- a/test/bp_2site.jl +++ b/test/bp_2site.jl @@ -8,7 +8,7 @@ Instance below looks like this: 56 -- 78 """ -function create_larger_example_factor_graph_tree_2site() +function create_larger_example_clustered_hamiltonian_tree_2site() instance = Dict( (1, 1) => 0.50, (2, 2) => -0.25, @@ -51,21 +51,21 @@ function create_larger_example_factor_graph_tree_2site() 8 => (2, 2, 2) ) - fg1 = factor_graph( + cl_h1 = clustered_hamiltonian( ig, Dict{NTuple{2, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule1, ) - fg2 = factor_graph( + cl_h2 = clustered_hamiltonian( ig, Dict{NTuple{3, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule2, ) - ig, fg1, fg2 + ig, cl_h1, cl_h2 end """ @@ -78,7 +78,7 @@ Instance below looks like this: 10 """ -function create_larger_example_factor_graph_tree_2site_pathological() +function create_larger_example_clustered_hamiltonian_tree_2site_pathological() instance = Dict( (1, 1) => -0.50, (2, 2) => 0.25, @@ -131,62 +131,62 @@ function create_larger_example_factor_graph_tree_2site_pathological() 10 => (3, 2, 2) ) - fg1 = factor_graph( + cl_h1 = clustered_hamiltonian( ig, Dict{NTuple{2, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule1, ) - fg2 = factor_graph( + cl_h2 = clustered_hamiltonian( ig, Dict{NTuple{3, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule2, ) - ig, fg1, fg2 + ig, cl_h1, cl_h2 end @testset "Belief propagation 2site" begin - for (ig, fg1, fg2) ∈ [create_larger_example_factor_graph_tree_2site(), - create_larger_example_factor_graph_tree_2site_pathological()] + for (ig, cl_h1, cl_h2) ∈ [create_larger_example_clustered_hamiltonian_tree_2site(), + create_larger_example_clustered_hamiltonian_tree_2site_pathological()] for beta ∈ [0.6, 1.1] tol = 1e-12 iter = 16 num_states=10 - new_fg1 = factor_graph_2site(fg2, beta) + new_cl_h1 = clustered_hamiltonian_2site(cl_h2, beta) - @test vertices(new_fg1) == vertices(fg1) - @test edges(new_fg1) == edges(fg1) - for e ∈ vertices(new_fg1) - @test get_prop(new_fg1, e, :spectrum).energies ≈ get_prop(fg1, e, :spectrum).energies + @test vertices(new_cl_h1) == vertices(cl_h1) + @test edges(new_cl_h1) == edges(cl_h1) + for e ∈ vertices(new_cl_h1) + @test get_prop(new_cl_h1, e, :spectrum).energies ≈ get_prop(cl_h1, e, :spectrum).energies end - for e ∈ edges(new_fg1) - E = get_prop(new_fg1, src(e), dst(e), :en) + for e ∈ edges(new_cl_h1) + E = get_prop(new_cl_h1, src(e), dst(e), :en) @cast E[(l1, l2), (r1, r2)] := E.e11[l1, r1] + E.e21[l2, r1] + E.e12[l1, r2] + E.e22[l2, r2] - @test E == get_prop(fg1, src(e), dst(e), :en) + @test E == get_prop(cl_h1, src(e), dst(e), :en) end - for e ∈ edges(new_fg1) - @test get_prop(new_fg1, src(e), dst(e), :pl) == get_prop(fg1, src(e), dst(e), :pl) - @test get_prop(new_fg1, src(e), dst(e), :pr) == get_prop(fg1, src(e), dst(e), :pr) + for e ∈ edges(new_cl_h1) + @test get_prop(new_cl_h1, src(e), dst(e), :pl) == get_prop(cl_h1, src(e), dst(e), :pl) + @test get_prop(new_cl_h1, src(e), dst(e), :pr) == get_prop(cl_h1, src(e), dst(e), :pr) end - beliefs = belief_propagation(new_fg1, beta; iter=iter, tol=tol) + beliefs = belief_propagation(new_cl_h1, beta; iter=iter, tol=tol) exact_marginal = Dict() for k in keys(beliefs) - temp = -1/beta .* log.([exact_cond_prob(fg1, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) + temp = -1/beta .* log.([exact_cond_prob(cl_h1, beta, Dict(k => a)) for a in 1:length(beliefs[k])]) push!(exact_marginal, k => temp .- minimum(temp)) end for v in keys(beliefs) @test beliefs[v] ≈ exact_marginal[v] end - truncate_factor_graph_2site_BP(fg2, beliefs, num_states; beta=beta) + truncate_clustered_hamiltonian_2site_BP(cl_h2, beliefs, num_states; beta=beta) end end end diff --git a/test/factor.jl b/test/clustered_hamiltonian.jl similarity index 77% rename from test/factor.jl rename to test/clustered_hamiltonian.jl index 8750699..c11273f 100644 --- a/test/factor.jl +++ b/test/clustered_hamiltonian.jl @@ -14,16 +14,16 @@ enum(vec) = Dict(v => i for (i, v) ∈ enumerate(vec)) ig = ising_graph(instance) - fg = factor_graph(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t)) ) + cl_h = clustered_hamiltonian(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t)) ) - @test collect(vertices(fg)) == [(i, j) for i ∈ 1:m for j ∈ 1:n] + @test collect(vertices(cl_h)) == [(i, j) for i ∈ 1:m for j ∈ 1:n] clv = [] cle = [] rank = rank_vec(ig) - for v ∈ vertices(fg) - cl = get_prop(fg, v, :cluster) + for v ∈ vertices(cl_h) + cl = get_prop(cl_h, v, :cluster) push!(clv, vertices(cl)) push!(cle, collect(edges(cl))) @@ -80,19 +80,19 @@ end bond_dimensions = [2, 2, 8, 4, 2, 2, 8] - fg = factor_graph( + cl_h = clustered_hamiltonian( ising_graph(instance), spectrum=full_spectrum, cluster_assignment_rule=super_square_lattice((m, n, t)), ) - for (bd, e) in zip(bond_dimensions, edges(fg)) - pl, en, pr = get_prop(fg, e, :pl), get_prop(fg, e, :en), get_prop(fg, e, :pr) + for (bd, e) in zip(bond_dimensions, edges(cl_h)) + pl, en, pr = get_prop(cl_h, e, :pl), get_prop(cl_h, e, :en), get_prop(cl_h, e, :pr) @test minimum(size(en)) == bd end for ((i, j), cedge) ∈ cedges - pl, en, pr = get_prop(fg, i, j, :pl), get_prop(fg, i, j, :en), get_prop(fg, i, j, :pr) + pl, en, pr = get_prop(cl_h, i, j, :pl), get_prop(cl_h, i, j, :en), get_prop(cl_h, i, j, :pr) base_i = all_states(rank[i]) base_j = all_states(rank[j]) @@ -118,23 +118,23 @@ end end @testset "each cluster comprises expected cells" begin - for v ∈ vertices(fg) - cl = get_prop(fg, v, :cluster) + for v ∈ vertices(cl_h) + cl = get_prop(cl_h, v, :cluster) @test issetequal(vertices(cl), cells[v]) end end @testset "each edge comprises expected bunch of edges from source Ising graph" begin - for e ∈ edges(fg) - outer_edges = get_prop(fg, e, :outer_edges) + for e ∈ edges(cl_h) + outer_edges = get_prop(cl_h, e, :outer_edges) @test issetequal(cedges[(src(e), dst(e))], [(src(oe), dst(oe)) for oe ∈ outer_edges]) end end end -function create_example_factor_graph() +function create_example_clustered_hamiltonian() J12 = -1.0 h1 = 0.5 h2 = 0.75 @@ -142,7 +142,7 @@ function create_example_factor_graph() D = Dict((1, 2) => J12, (1, 1) => h1, (2, 2) => h2) ig = ising_graph(D) - factor_graph( + clustered_hamiltonian( ig, Dict((1, 1) => 2, (1, 2) => 2), spectrum = full_spectrum, @@ -150,14 +150,14 @@ function create_example_factor_graph() ) end -fg_state_to_spin = [ +cl_h_state_to_spin = [ ([1, 1], [-1, -1]), ([1, 2], [-1, 1]), ([2, 1], [1, -1]), ([2, 2], [1, 1]) ] @testset "Decoding solution gives correct spin assignment" begin - fg = create_example_factor_graph() - for (state, spin_values) ∈ fg_state_to_spin - d = decode_factor_graph_state(fg, state) + cl_h = create_example_clustered_hamiltonian() + for (state, spin_values) ∈ cl_h_state_to_spin + d = decode_clustered_hamiltonian_state(cl_h, state) states = collect(values(d))[collect(keys(d))] @test states == spin_values end @@ -174,7 +174,7 @@ Instance below looks like this: And we group the following spins together: [1, 2, 4, 5], [3, 6], [7, 8], [9]. """ -function create_larger_example_factor_graph() +function create_larger_example_clustered_hamiltonian() instance = Dict( (1, 1) => 0.5, (2, 2) => 0.25, @@ -213,30 +213,30 @@ function create_larger_example_factor_graph() 9 => (2, 2) ) - fg = factor_graph( + cl_h = clustered_hamiltonian( ig, Dict{NTuple{2, Int}, Int}(), spectrum = full_spectrum, cluster_assignment_rule = assignment_rule, ) - ig, fg + ig, cl_h end -function factor_graph_energy(fg, state) +function clustered_hamiltonian_energy(cl_h, state) # This is highly inefficient, but simple, which makes it suitable for testing. # If such a function is needed elsewhere, we need to implement it properly. total_en = 0.0 # Collect local terms from each cluster - for (s, v) ∈ zip(state, vertices(fg)) - total_en += get_prop(fg, v, :spectrum).energies[s] + for (s, v) ∈ zip(state, vertices(cl_h)) + total_en += get_prop(cl_h, v, :spectrum).energies[s] end # Collect inter-cluster terms - for edge ∈ edges(fg) - i, j = fg.reverse_label_map[src(edge)], fg.reverse_label_map[dst(edge)] - pl, en, pr = get_prop(fg, edge, :pl), get_prop(fg, edge, :en), get_prop(fg, edge, :pr) + for edge ∈ edges(cl_h) + i, j = cl_h.reverse_label_map[src(edge)], cl_h.reverse_label_map[dst(edge)] + pl, en, pr = get_prop(cl_h, edge, :pl), get_prop(cl_h, edge, :en), get_prop(cl_h, edge, :pr) edge_energy = en[pl, pr] total_en += edge_energy[state[i], state[j]] end @@ -246,17 +246,17 @@ end @testset "Decoding solution gives spins configuration with corresponding energies" begin - ig, fg = create_larger_example_factor_graph() + ig, cl_h = create_larger_example_clustered_hamiltonian() # Corresponding bases sizes for each cluster are 16, 4, 4, 2. all_states = [[i, j, k, l] for i ∈ 1:16 for j ∈ 1:4 for k ∈ 1:4 for l ∈ 1:2] for state ∈ all_states - d = decode_factor_graph_state(fg, state) + d = decode_clustered_hamiltonian_state(cl_h, state) spins = zeros(length(d)) for (k, v) ∈ d spins[k] = v end - @test factor_graph_energy(fg, state) ≈ energy([Int.(spins)], ig)[] + @test clustered_hamiltonian_energy(cl_h, state) ≈ energy([Int.(spins)], ig)[] end end diff --git a/test/runtests.jl b/test/runtests.jl index 22efa5d..31dc807 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -29,7 +29,7 @@ end my_tests = [ "ising.jl", - "factor.jl", + "clustered_hamiltonian.jl", "bp_1site.jl", "bp_2site.jl", "utils.jl" diff --git a/test/spectrum.jl b/test/spectrum.jl new file mode 100644 index 0000000..14f9d21 --- /dev/null +++ b/test/spectrum.jl @@ -0,0 +1,8 @@ +# vector_of_vectors = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] + +# matrix = transpose(hcat(vector_of_vectors...)) +# println(matrix) + +A = [[-1, -1], [1, -1], [1, 1], [-1, 1]] +println(typeof(Array(A))) +println(matrix_to_integers(A)) \ No newline at end of file diff --git a/test/utils.jl b/test/utils.jl index 86766aa..acc07ef 100644 --- a/test/utils.jl +++ b/test/utils.jl @@ -77,18 +77,18 @@ end # max_cl_states = 2 # ig = ising_graph(joinpath(instance_dir, instance)) -# fg = factor_graph( +# cl_h = clustered_hamiltonian( # ig, # max_cl_states, # spectrum = brute_force, # cluster_assignment_rule=super_square_lattice((m, n, t)) # ) -# @test nv(fg) == s^2 +# @test nv(cl_h) == s^2 # if s > 1 # for l in 1:s-1, k in 2:s -# @test has_edge(fg, (l,k), (l+1,k-1)) +# @test has_edge(cl_h, (l,k), (l+1,k-1)) # end # end # end From 8ec1276a603e1e430a018ebad4467d40003a95db Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Tue, 19 Sep 2023 10:38:18 +0200 Subject: [PATCH 166/218] add bond energy --- src/bp.jl | 5 +++-- src/clustered_hamiltonian.jl | 20 ++++++++++++++++++-- 2 files changed, 21 insertions(+), 4 deletions(-) diff --git a/src/bp.jl b/src/bp.jl index eb34e9b..60a7ce2 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -1,7 +1,8 @@ export belief_propagation, - clustered_hamiltonian_2site + clustered_hamiltonian_2site, + projector function belief_propagation(cl_h, beta; tol=1e-6, iter=1) @@ -227,7 +228,7 @@ function interaction_energy(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::N end end -function projector(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} +function projector(cl_h::LabelledGraph{S, T}, v::NTuple{N, Int64}, w::NTuple{N, Int64}) where {S, T, N} if has_edge(cl_h, w, v) p = get_prop(cl_h, w, v, :pr) elseif has_edge(cl_h, v, w) diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index 533a79e..f0f8f50 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -1,14 +1,14 @@ export clustered_hamiltonian, rank_reveal, - projectors, split_into_clusters, decode_clustered_hamiltonian_state, energy, energy_2site, cluster_size, truncate_clustered_hamiltonian, - exact_cond_prob + exact_cond_prob, + bond_energy """ Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) """ @@ -155,6 +155,22 @@ function energy_2site(cl_h::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} int_eng end +function bond_energy(cl_h::LabelledGraph{S, T}, cl_h_u::NTuple{N, Int64}, cl_h_v::NTuple{N, Int64}, σ::Int) where {S, T, N} + if has_edge(cl_h, cl_h_u, cl_h_v) + pu, en, pv = get_prop.( + Ref(cl_h), Ref(cl_h_u), Ref(cl_h_v), (:pl, :en, :pr) + ) + @inbounds energies = en[pu, pv[σ]] + elseif has_edge(cl_h, cl_h_v, cl_h_u) + pv, en, pu = get_prop.( + Ref(cl_h), Ref(cl_h_v), Ref(cl_h_u), (:pl, :en, :pr) + ) + @inbounds energies = en[pv[σ], pu] + else + energies = zeros(cluster_size(cl_h, cl_h_u)) + end +end + function cluster_size(clustered_hamiltonian::LabelledGraph{S, T}, vertex::T) where {S, T} length(get_prop(clustered_hamiltonian, vertex, :spectrum).energies) end From 1bd2552f3cf26a19578752396835d7d8abeb781e Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Tue, 19 Sep 2023 20:01:25 +0200 Subject: [PATCH 167/218] try to move PoolOfProjectors --- src/SpinGlassNetworks.jl | 1 + src/clustered_hamiltonian.jl | 65 ++++++++++++++++++++++++++++++ src/projectors.jl | 78 ++++++++++++++++++++++++++++++++++++ 3 files changed, 144 insertions(+) create mode 100644 src/projectors.jl diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 264030c..cacfa42 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -88,6 +88,7 @@ module SpinGlassNetworks include("ising.jl") include("spectrum.jl") include("lattice.jl") + include("projectors.jl") include("clustered_hamiltonian.jl") include("bp.jl") include("truncate.jl") diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index f0f8f50..1d4f322 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -32,6 +32,62 @@ function clustered_hamiltonian( clustered_hamiltonian(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end +# function clustered_hamiltonian( +# ig::IsingGraph, +# num_states_cl::Dict{T, Int}; +# spectrum::Function=full_spectrum, +# cluster_assignment_rule::Dict{Int, T} +# ) where T +# L = maximum(values(cluster_assignment_rule)) +# cl_h = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) +# lp = PoolOfProjectors2{Int}() + +# for (v, cl) ∈ split_into_clusters(ig, cluster_assignment_rule) +# sp = spectrum(cl, num_states=get(num_states_cl, v, basis_size(cl))) +# set_props!(cl_h, v, Dict(:cluster => cl, :spectrum => sp)) +# end + +# for (i, v) ∈ enumerate(vertices(cl_h)), w ∈ vertices(cl_h)[i+1:end] +# cl1, cl2 = get_prop(cl_h, v, :cluster), get_prop(cl_h, w, :cluster) +# outer_edges, J = inter_cluster_edges(ig, cl1, cl2) + +# if !isempty(outer_edges) +# ind1 = any(i -> i != 0, J, dims=2) +# ind2 = any(i -> i != 0, J, dims=1) +# ind1 = reshape(ind1, length(ind1)) +# ind2 = reshape(ind2, length(ind2)) +# JJ = J[ind1, ind2] + +# states_v = get_prop(cl_h, v, :spectrum).states +# states_w = get_prop(cl_h, w, :spectrum).states + +# pl, unique_states_v = rank_reveal([s[ind1] for s ∈ states_v], :PE) +# pr, unique_states_w = rank_reveal([s[ind2] for s ∈ states_w], :PE) +# en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) +# add_projector2!(lp, pl) +# add_edge!(cl_h, v, w) +# set_props!( +# cl_h, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) +# ) +# end +# end +# cl_h +# end + +function get_projector_index(lp::PoolOfProjectors2{T}, proj::Proj{T}) where T + for (device, device_data) in lp.data + for (size, proj_dict) in device_data + for (index, p) in enumerate(proj_dict) + if p == proj + return index + end + end + end + end + return 0 # Return 0 if the projector is not found +end + + function clustered_hamiltonian( ig::IsingGraph, num_states_cl::Dict{T, Int}; @@ -40,6 +96,7 @@ function clustered_hamiltonian( ) where T L = maximum(values(cluster_assignment_rule)) cl_h = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) + lp = PoolOfProjectors2{Int}() for (v, cl) ∈ split_into_clusters(ig, cluster_assignment_rule) sp = spectrum(cl, num_states=get(num_states_cl, v, basis_size(cl))) @@ -63,13 +120,21 @@ function clustered_hamiltonian( pl, unique_states_v = rank_reveal([s[ind1] for s ∈ states_v], :PE) pr, unique_states_w = rank_reveal([s[ind2] for s ∈ states_w], :PE) en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) + add_projector2!(lp, pl) + add_projector2!(lp, pr) + ipl = get_projector_index(lp, pl) + ipr = get_projector_index(lp, pr) add_edge!(cl_h, v, w) set_props!( cl_h, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) ) + set_props!( + cl_h, v, w, Dict(:outer_edges => outer_edges, :ipl => ipl, :en => en, :ipr => ipr) + ) end end + set_props!(cl_h, Dict(:pool_of_projectors => lp)) cl_h end diff --git a/src/projectors.jl b/src/projectors.jl new file mode 100644 index 0000000..30a4b74 --- /dev/null +++ b/src/projectors.jl @@ -0,0 +1,78 @@ +export + PoolOfProjectors2, + get_projector2!, + add_projector2! + +const Proj{T} = Union{Vector{T}, Array{T, 1}} + +struct PoolOfProjectors2{T <: Integer} + data::Dict{Symbol, Dict{Int, Proj{T}}} + default_device::Symbol + sizes::Dict{Int, Int} + + PoolOfProjectors2(data::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(Dict(:CPU => data), + :CPU, + Dict{Int, Int}(k => maximum(v) for (k, v) ∈ data)) + PoolOfProjectors2{T}() where T = new{T}(Dict(:CPU => Dict{Int, Proj{T}}()), + :CPU, + Dict{Int, Int}()) +end + + +Base.eltype(lp::PoolOfProjectors2{T}) where T = T +Base.length(lp::PoolOfProjectors2) = length(lp.data[lp.default_device]) +Base.length(lp::PoolOfProjectors2, device::Symbol) = length(lp.data[device]) + +function Base.empty!(lp::PoolOfProjectors2, device::Symbol) + if device ∈ keys(lp.data) + empty!(lp.data[device]) + end +end + +Base.length(lp::PoolOfProjectors2, index::Int) = length(lp.data[lp.default_device][index]) +Base.size(lp::PoolOfProjectors2, index::Int) = lp.sizes[index] + +get_projector2!(lp::PoolOfProjectors2, index::Int) = get_projector2!(lp, index, lp.default_device) + +# TODO This is version for only one GPU +function get_projector2!(lp::PoolOfProjectors2{T}, index::Int, device::Symbol) where T <: Integer + if device ∉ keys(lp.data) + push!(lp.data, device => Dict{Int, Proj{T}}()) + end + + if index ∉ keys(lp.data[device]) + if device == :GPU + p = CuArray{T}(lp.data[lp.default_device][index]) + elseif device == :CPU + p = Array{T}(lp.data[lp.default_device][index]) + else + throw(ArgumentError("device should be :CPU or :GPU")) + end + push!(lp.data[device], index => p) + end + lp.data[device][index] +end + +function add_projector2!(lp::PoolOfProjectors2{T}, p::Proj) where T <: Integer + if lp.default_device == :CPU + p = Array{T}(p) + elseif lp.default_device == :GPU + p = CuArray{T}(p) + else + throw(ArgumentError("default_device should be :CPU or :GPU")) + end + if p in values(lp.data[lp.default_device]) + key = -1 + for guess in keys(lp.data[lp.default_device]) + if lp.data[lp.default_device][guess] == p + key = guess + break + end + end + else + key = length(lp.data[lp.default_device]) + 1 + push!(lp.data[lp.default_device], key => p) + push!(lp.sizes, key => maximum(p)) + end + key +end From a3d865bdb296971266fb3afaffa4d3dc9165d346 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 20 Sep 2023 11:05:29 +0200 Subject: [PATCH 168/218] add CUDA --- Project.toml | 2 ++ src/SpinGlassNetworks.jl | 1 + 2 files changed, 3 insertions(+) diff --git a/Project.toml b/Project.toml index 3abd888..5f14176 100644 --- a/Project.toml +++ b/Project.toml @@ -12,6 +12,8 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2" MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5" SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf" +NNlibCUDA = "a00861dc-f156-4864-bf3c-e6376f28a68d" +CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" [compat] CSV = "0.8" diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index cacfa42..2d6a1be 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -7,6 +7,7 @@ module SpinGlassNetworks using LinearAlgebra, MKL using Base.Cartesian using SparseArrays + using CUDA, CUDA.CUSPARSE import Base.Prehashed From 5ace38454454837f44fe02065b2edf0e0b041460 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 20 Sep 2023 12:47:16 +0200 Subject: [PATCH 169/218] try to remove :pl, :pr --- src/bp.jl | 10 ++++-- src/clustered_hamiltonian.jl | 63 +++++++++++++++++++---------------- test/clustered_hamiltonian.jl | 13 ++++++-- 3 files changed, 52 insertions(+), 34 deletions(-) diff --git a/src/bp.jl b/src/bp.jl index 60a7ce2..eb3d754 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -72,10 +72,14 @@ function get_neighbors(cl_h::LabelledGraph{S, T}, vertex::NTuple) where {S, T} if src_node == vertex en = get_prop(cl_h, src_node, dst_node, :en) pv = get_prop(cl_h, src_node, dst_node, :pl) + # idx_pv = get_prop(cl_h, src_node, dst_node, :ipl) + # pv = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) push!(neighbors, (dst_node, pv, en)) elseif dst_node == vertex en = get_prop(cl_h, src_node, dst_node, :en)' pv = get_prop(cl_h, src_node, dst_node, :pr) + # idx_pv = get_prop(cl_h, src_node, dst_node, :ipr) + # pv = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) push!(neighbors, (src_node, pv, en)) end end @@ -230,9 +234,11 @@ end function projector(cl_h::LabelledGraph{S, T}, v::NTuple{N, Int64}, w::NTuple{N, Int64}) where {S, T, N} if has_edge(cl_h, w, v) - p = get_prop(cl_h, w, v, :pr) + idx_p = get_prop(cl_h, w, v, :ipr) + p = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_p, :CPU) elseif has_edge(cl_h, v, w) - p = get_prop(cl_h, v, w, :pl) + idx_p = get_prop(cl_h, v, w, :ipl) + p = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_p, :CPU) else p = ones(Int, v ∈ vertices(cl_h) ? length(get_prop(cl_h, v, :spectrum).energies) : 1) end diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index 1d4f322..318916a 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -74,19 +74,6 @@ end # cl_h # end -function get_projector_index(lp::PoolOfProjectors2{T}, proj::Proj{T}) where T - for (device, device_data) in lp.data - for (size, proj_dict) in device_data - for (index, p) in enumerate(proj_dict) - if p == proj - return index - end - end - end - end - return 0 # Return 0 if the projector is not found -end - function clustered_hamiltonian( ig::IsingGraph, @@ -120,10 +107,8 @@ function clustered_hamiltonian( pl, unique_states_v = rank_reveal([s[ind1] for s ∈ states_v], :PE) pr, unique_states_w = rank_reveal([s[ind2] for s ∈ states_w], :PE) en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) - add_projector2!(lp, pl) - add_projector2!(lp, pr) - ipl = get_projector_index(lp, pl) - ipr = get_projector_index(lp, pr) + ipl = add_projector2!(lp, pl) + ipr = add_projector2!(lp, pr) add_edge!(cl_h, v, w) set_props!( @@ -194,7 +179,10 @@ function energy(cl_h::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_cl_h = 0.0 for v ∈ vertices(cl_h) en_cl_h += get_prop(cl_h, v, :spectrum).energies[σ[v]] end for edge ∈ edges(cl_h) - pl, pr = get_prop(cl_h, edge, :pl), get_prop(cl_h, edge, :pr) + idx_pl = get_prop(cl_h, edge, :ipl) + pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pl, :CPU) + idx_pr = get_prop(cl_h, edge, :ipr) + pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pr, :CPU) en = get_prop(cl_h, edge, :en) en_cl_h += en[pl[σ[src(edge)]], pr[σ[dst(edge)]]] end @@ -206,13 +194,17 @@ function energy_2site(cl_h::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} # matrix of interaction energies between two nodes if has_edge(cl_h, (i, j, 1), (i, j, 2)) en12 = copy(get_prop(cl_h, (i, j, 1), (i, j, 2), :en)) - pl = copy(get_prop(cl_h, (i, j, 1), (i, j, 2), :pl)) - pr = copy(get_prop(cl_h, (i, j, 1), (i, j, 2), :pr)) + idx_pl = get_prop(cl_h, (i, j, 1), (i, j, 2), :ipl) + pl = copy(get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pl, :CPU)) + idx_pr = get_prop(cl_h, (i, j, 1), (i, j, 2), :ipr) + pr = copy(get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pr, :CPU)) int_eng = en12[pl, pr] elseif has_edge(cl_h, (i, j, 2), (i, j, 1)) en21 = copy(get_prop(cl_h, (i, j, 2), (i, j, 1), :en)) - pl = copy(get_prop(cl_h, (i, j, 2), (i, j, 1), :pl)) - pr = copy(get_prop(cl_h, (i, j, 2), (i, j, 1), :pr)) + idx_pl = get_prop(cl_h, (i, j, 2), (i, j, 1), :ipl) + pl = copy(get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pl, :CPU)) + idx_pr = get_prop(cl_h, (i, j, 2), (i, j, 1), :ipr) + pr = copy(get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pr, :CPU)) int_eng = en21[pl, pr]' else int_eng = zeros(1, 1) @@ -222,14 +214,18 @@ end function bond_energy(cl_h::LabelledGraph{S, T}, cl_h_u::NTuple{N, Int64}, cl_h_v::NTuple{N, Int64}, σ::Int) where {S, T, N} if has_edge(cl_h, cl_h_u, cl_h_v) - pu, en, pv = get_prop.( - Ref(cl_h), Ref(cl_h_u), Ref(cl_h_v), (:pl, :en, :pr) + ipu, en, ipv = get_prop.( + Ref(cl_h), Ref(cl_h_u), Ref(cl_h_v), (:ipl, :en, :ipr) ) + pu = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipu, :CPU) + pv = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipv, :CPU) @inbounds energies = en[pu, pv[σ]] elseif has_edge(cl_h, cl_h_v, cl_h_u) - pv, en, pu = get_prop.( - Ref(cl_h), Ref(cl_h_v), Ref(cl_h_u), (:pl, :en, :pr) + ipv, en, ipu = get_prop.( + Ref(cl_h), Ref(cl_h_v), Ref(cl_h_u), (:ipl, :en, :ipr) ) + pu = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipu, :CPU) + pv = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipv, :CPU) @inbounds energies = en[pv[σ], pu] else energies = zeros(cluster_size(cl_h, cl_h_u)) @@ -253,6 +249,7 @@ function exact_cond_prob(clustered_hamiltonian::LabelledGraph{S, T}, beta, targe function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) where {S, T} new_cl_h = LabelledGraph{MetaDiGraph}(vertices(cl_h)) + new_lp = PoolOfProjectors2{Int}() for v ∈ vertices(new_cl_h) cl = get_prop(cl_h, v, :cluster) @@ -269,18 +266,26 @@ function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) v, w = src(e), dst(e) add_edge!(new_cl_h, v, w) outer_edges = get_prop(cl_h, v, w, :outer_edges) - pl = get_prop(cl_h, v, w, :pl) - pr = get_prop(cl_h, v, w, :pr) + ipl = get_prop(cl_h, v, w, :ipl) + pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) + ipr = get_prop(cl_h, v, w, :ipr) + pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) en = get_prop(cl_h, v, w, :en) pl = pl[states[v]] pr = pr[states[w]] pl_transition, pl_unique = rank_reveal(pl, :PE) pr_transition, pr_unique = rank_reveal(pr, :PE) en = en[pl_unique, pr_unique] - + ipl = add_projector2!(new_lp, pl_transition) + ipr = add_projector2!(new_lp, pr_transition) + set_props!( + new_cl_h, v, w, Dict(:outer_edges => outer_edges, :ipl => ipl, :en => en, :ipr => ipr) + ) set_props!( new_cl_h, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) ) end + set_props!(new_cl_h, Dict(:pool_of_projectors => new_lp)) + new_cl_h end diff --git a/test/clustered_hamiltonian.jl b/test/clustered_hamiltonian.jl index c11273f..01381e0 100644 --- a/test/clustered_hamiltonian.jl +++ b/test/clustered_hamiltonian.jl @@ -87,12 +87,17 @@ end ) for (bd, e) in zip(bond_dimensions, edges(cl_h)) - pl, en, pr = get_prop(cl_h, e, :pl), get_prop(cl_h, e, :en), get_prop(cl_h, e, :pr) + ipl, en, ipr = get_prop(cl_h, e, :ipl), get_prop(cl_h, e, :en), get_prop(cl_h, e, :ipr) + pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) + pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) + @test minimum(size(en)) == bd end for ((i, j), cedge) ∈ cedges - pl, en, pr = get_prop(cl_h, i, j, :pl), get_prop(cl_h, i, j, :en), get_prop(cl_h, i, j, :pr) + ipl, en, ipr = get_prop(cl_h, i, j, :ipl), get_prop(cl_h, i, j, :en), get_prop(cl_h, i, j, :ipr) + pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) + pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) base_i = all_states(rank[i]) base_j = all_states(rank[j]) @@ -236,7 +241,9 @@ function clustered_hamiltonian_energy(cl_h, state) # Collect inter-cluster terms for edge ∈ edges(cl_h) i, j = cl_h.reverse_label_map[src(edge)], cl_h.reverse_label_map[dst(edge)] - pl, en, pr = get_prop(cl_h, edge, :pl), get_prop(cl_h, edge, :en), get_prop(cl_h, edge, :pr) + ipl, en, ipr = get_prop(cl_h, edge, :ipl), get_prop(cl_h, edge, :en), get_prop(cl_h, edge, :ipr) + pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) + pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) edge_energy = en[pl, pr] total_en += edge_energy[state[i], state[j]] end From 39a095fd4303c014012d85475e9f5e2a4481f276 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 20 Sep 2023 19:18:26 +0200 Subject: [PATCH 170/218] PoolOfProjectors in clustered_hamiltonian --- src/SpinGlassNetworks.jl | 1 - src/bp.jl | 8 ++-- src/clustered_hamiltonian.jl | 40 ++++++++-------- src/projectors.jl | 86 ++++++++++++++++++++++++++++------- test/clustered_hamiltonian.jl | 12 ++--- 5 files changed, 100 insertions(+), 47 deletions(-) diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index 2d6a1be..485d812 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -8,7 +8,6 @@ module SpinGlassNetworks using Base.Cartesian using SparseArrays using CUDA, CUDA.CUSPARSE - import Base.Prehashed export unique_neighbors diff --git a/src/bp.jl b/src/bp.jl index eb3d754..9c23842 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -73,13 +73,13 @@ function get_neighbors(cl_h::LabelledGraph{S, T}, vertex::NTuple) where {S, T} en = get_prop(cl_h, src_node, dst_node, :en) pv = get_prop(cl_h, src_node, dst_node, :pl) # idx_pv = get_prop(cl_h, src_node, dst_node, :ipl) - # pv = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) + # pv = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) push!(neighbors, (dst_node, pv, en)) elseif dst_node == vertex en = get_prop(cl_h, src_node, dst_node, :en)' pv = get_prop(cl_h, src_node, dst_node, :pr) # idx_pv = get_prop(cl_h, src_node, dst_node, :ipr) - # pv = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) + # pv = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) push!(neighbors, (src_node, pv, en)) end end @@ -235,10 +235,10 @@ end function projector(cl_h::LabelledGraph{S, T}, v::NTuple{N, Int64}, w::NTuple{N, Int64}) where {S, T, N} if has_edge(cl_h, w, v) idx_p = get_prop(cl_h, w, v, :ipr) - p = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_p, :CPU) + p = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_p, :CPU) elseif has_edge(cl_h, v, w) idx_p = get_prop(cl_h, v, w, :ipl) - p = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_p, :CPU) + p = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_p, :CPU) else p = ones(Int, v ∈ vertices(cl_h) ? length(get_prop(cl_h, v, :spectrum).energies) : 1) end diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index 318916a..51230b7 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -40,7 +40,7 @@ end # ) where T # L = maximum(values(cluster_assignment_rule)) # cl_h = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) -# lp = PoolOfProjectors2{Int}() +# lp = PoolOfProjectors{Int}() # for (v, cl) ∈ split_into_clusters(ig, cluster_assignment_rule) # sp = spectrum(cl, num_states=get(num_states_cl, v, basis_size(cl))) @@ -64,7 +64,7 @@ end # pl, unique_states_v = rank_reveal([s[ind1] for s ∈ states_v], :PE) # pr, unique_states_w = rank_reveal([s[ind2] for s ∈ states_w], :PE) # en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) -# add_projector2!(lp, pl) +# add_projector!(lp, pl) # add_edge!(cl_h, v, w) # set_props!( # cl_h, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) @@ -83,7 +83,7 @@ function clustered_hamiltonian( ) where T L = maximum(values(cluster_assignment_rule)) cl_h = LabelledGraph{MetaDiGraph}(sort(unique(values(cluster_assignment_rule)))) - lp = PoolOfProjectors2{Int}() + lp = PoolOfProjectors{Int}() for (v, cl) ∈ split_into_clusters(ig, cluster_assignment_rule) sp = spectrum(cl, num_states=get(num_states_cl, v, basis_size(cl))) @@ -107,8 +107,8 @@ function clustered_hamiltonian( pl, unique_states_v = rank_reveal([s[ind1] for s ∈ states_v], :PE) pr, unique_states_w = rank_reveal([s[ind2] for s ∈ states_w], :PE) en = inter_cluster_energy(unique_states_v, JJ, unique_states_w) - ipl = add_projector2!(lp, pl) - ipr = add_projector2!(lp, pr) + ipl = add_projector!(lp, pl) + ipr = add_projector!(lp, pr) add_edge!(cl_h, v, w) set_props!( @@ -180,9 +180,9 @@ function energy(cl_h::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} for v ∈ vertices(cl_h) en_cl_h += get_prop(cl_h, v, :spectrum).energies[σ[v]] end for edge ∈ edges(cl_h) idx_pl = get_prop(cl_h, edge, :ipl) - pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pl, :CPU) + pl = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pl, :CPU) idx_pr = get_prop(cl_h, edge, :ipr) - pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pr, :CPU) + pr = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pr, :CPU) en = get_prop(cl_h, edge, :en) en_cl_h += en[pl[σ[src(edge)]], pr[σ[dst(edge)]]] end @@ -195,16 +195,16 @@ function energy_2site(cl_h::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} if has_edge(cl_h, (i, j, 1), (i, j, 2)) en12 = copy(get_prop(cl_h, (i, j, 1), (i, j, 2), :en)) idx_pl = get_prop(cl_h, (i, j, 1), (i, j, 2), :ipl) - pl = copy(get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pl, :CPU)) + pl = copy(get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pl, :CPU)) idx_pr = get_prop(cl_h, (i, j, 1), (i, j, 2), :ipr) - pr = copy(get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pr, :CPU)) + pr = copy(get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pr, :CPU)) int_eng = en12[pl, pr] elseif has_edge(cl_h, (i, j, 2), (i, j, 1)) en21 = copy(get_prop(cl_h, (i, j, 2), (i, j, 1), :en)) idx_pl = get_prop(cl_h, (i, j, 2), (i, j, 1), :ipl) - pl = copy(get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pl, :CPU)) + pl = copy(get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pl, :CPU)) idx_pr = get_prop(cl_h, (i, j, 2), (i, j, 1), :ipr) - pr = copy(get_projector2!(get_prop(cl_h, :pool_of_projectors), idx_pr, :CPU)) + pr = copy(get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pr, :CPU)) int_eng = en21[pl, pr]' else int_eng = zeros(1, 1) @@ -217,15 +217,15 @@ function bond_energy(cl_h::LabelledGraph{S, T}, cl_h_u::NTuple{N, Int64}, cl_h_v ipu, en, ipv = get_prop.( Ref(cl_h), Ref(cl_h_u), Ref(cl_h_v), (:ipl, :en, :ipr) ) - pu = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipu, :CPU) - pv = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipv, :CPU) + pu = get_projector!(get_prop(cl_h, :pool_of_projectors), ipu, :CPU) + pv = get_projector!(get_prop(cl_h, :pool_of_projectors), ipv, :CPU) @inbounds energies = en[pu, pv[σ]] elseif has_edge(cl_h, cl_h_v, cl_h_u) ipv, en, ipu = get_prop.( Ref(cl_h), Ref(cl_h_v), Ref(cl_h_u), (:ipl, :en, :ipr) ) - pu = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipu, :CPU) - pv = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipv, :CPU) + pu = get_projector!(get_prop(cl_h, :pool_of_projectors), ipu, :CPU) + pv = get_projector!(get_prop(cl_h, :pool_of_projectors), ipv, :CPU) @inbounds energies = en[pv[σ], pu] else energies = zeros(cluster_size(cl_h, cl_h_u)) @@ -249,7 +249,7 @@ function exact_cond_prob(clustered_hamiltonian::LabelledGraph{S, T}, beta, targe function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) where {S, T} new_cl_h = LabelledGraph{MetaDiGraph}(vertices(cl_h)) - new_lp = PoolOfProjectors2{Int}() + new_lp = PoolOfProjectors{Int}() for v ∈ vertices(new_cl_h) cl = get_prop(cl_h, v, :cluster) @@ -267,17 +267,17 @@ function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) add_edge!(new_cl_h, v, w) outer_edges = get_prop(cl_h, v, w, :outer_edges) ipl = get_prop(cl_h, v, w, :ipl) - pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) + pl = get_projector!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) ipr = get_prop(cl_h, v, w, :ipr) - pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) + pr = get_projector!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) en = get_prop(cl_h, v, w, :en) pl = pl[states[v]] pr = pr[states[w]] pl_transition, pl_unique = rank_reveal(pl, :PE) pr_transition, pr_unique = rank_reveal(pr, :PE) en = en[pl_unique, pr_unique] - ipl = add_projector2!(new_lp, pl_transition) - ipr = add_projector2!(new_lp, pr_transition) + ipl = add_projector!(new_lp, pl_transition) + ipr = add_projector!(new_lp, pr_transition) set_props!( new_cl_h, v, w, Dict(:outer_edges => outer_edges, :ipl => ipl, :en => en, :ipr => ipr) ) diff --git a/src/projectors.jl b/src/projectors.jl index 30a4b74..53a80d0 100644 --- a/src/projectors.jl +++ b/src/projectors.jl @@ -1,41 +1,41 @@ export - PoolOfProjectors2, - get_projector2!, - add_projector2! + PoolOfProjectors, + get_projector!, + add_projector! -const Proj{T} = Union{Vector{T}, Array{T, 1}} +const Proj{T} = Union{Vector{T}, CuArray{T, 1}} -struct PoolOfProjectors2{T <: Integer} +struct PoolOfProjectors{T <: Integer} data::Dict{Symbol, Dict{Int, Proj{T}}} default_device::Symbol sizes::Dict{Int, Int} - PoolOfProjectors2(data::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(Dict(:CPU => data), + PoolOfProjectors(data::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(Dict(:CPU => data), :CPU, Dict{Int, Int}(k => maximum(v) for (k, v) ∈ data)) - PoolOfProjectors2{T}() where T = new{T}(Dict(:CPU => Dict{Int, Proj{T}}()), + PoolOfProjectors{T}() where T = new{T}(Dict(:CPU => Dict{Int, Proj{T}}()), :CPU, Dict{Int, Int}()) end -Base.eltype(lp::PoolOfProjectors2{T}) where T = T -Base.length(lp::PoolOfProjectors2) = length(lp.data[lp.default_device]) -Base.length(lp::PoolOfProjectors2, device::Symbol) = length(lp.data[device]) +Base.eltype(lp::PoolOfProjectors{T}) where T = T +Base.length(lp::PoolOfProjectors) = length(lp.data[lp.default_device]) +Base.length(lp::PoolOfProjectors, device::Symbol) = length(lp.data[device]) -function Base.empty!(lp::PoolOfProjectors2, device::Symbol) +function Base.empty!(lp::PoolOfProjectors, device::Symbol) if device ∈ keys(lp.data) empty!(lp.data[device]) end end -Base.length(lp::PoolOfProjectors2, index::Int) = length(lp.data[lp.default_device][index]) -Base.size(lp::PoolOfProjectors2, index::Int) = lp.sizes[index] +Base.length(lp::PoolOfProjectors, index::Int) = length(lp.data[lp.default_device][index]) +Base.size(lp::PoolOfProjectors, index::Int) = lp.sizes[index] -get_projector2!(lp::PoolOfProjectors2, index::Int) = get_projector2!(lp, index, lp.default_device) +get_projector!(lp::PoolOfProjectors, index::Int) = get_projector!(lp, index, lp.default_device) # TODO This is version for only one GPU -function get_projector2!(lp::PoolOfProjectors2{T}, index::Int, device::Symbol) where T <: Integer +function get_projector!(lp::PoolOfProjectors{T}, index::Int, device::Symbol) where T <: Integer if device ∉ keys(lp.data) push!(lp.data, device => Dict{Int, Proj{T}}()) end @@ -53,7 +53,7 @@ function get_projector2!(lp::PoolOfProjectors2{T}, index::Int, device::Symbol) w lp.data[device][index] end -function add_projector2!(lp::PoolOfProjectors2{T}, p::Proj) where T <: Integer +function add_projector!(lp::PoolOfProjectors{T}, p::Proj) where T <: Integer if lp.default_device == :CPU p = Array{T}(p) elseif lp.default_device == :GPU @@ -76,3 +76,57 @@ function add_projector2!(lp::PoolOfProjectors2{T}, p::Proj) where T <: Integer end key end + +# get_projector!(lp::PoolOfProjectors, index::Int) = get_projector!(lp, index, lp.default_device) + +# # TODO This is version for only one GPU +# function get_projector!(lp::PoolOfProjectors{T}, index::Int, ::Val{:CPU}) where T <: Integer +# device = :CPU +# if device ∉ keys(lp.data) +# push!(lp.data, device => Dict{Int, Proj{T}}()) +# end + +# if index ∉ keys(lp.data[device]) +# if device == :GPU +# p = CuArray{T}(lp.data[lp.default_device][index]) +# elseif device == :CPU +# p = Array{T}(lp.data[lp.default_device][index]) +# else +# throw(ArgumentError("device should be :CPU or :GPU")) +# end +# push!(lp.data[device], index => p) +# end +# lp.data[device][index] +# end + + +# add_projector!(lp::PoolOfProjectors, p::Proj) = add_projector!(lp::PoolOfProjectors, p::Proj, lp.default_device) + +# function add_projector!(lp::PoolOfProjectors{T}, p::Proj, device::Symbol) where T <: Integer +# if device == :CPU +# return add_projector!(lp::PoolOfProjectors, p::Proj, Val(device)) +# elseif device == :GPU +# return SpinGlassTensors.add_projector!(lp::PoolOfProjectors, p::Proj, Val(device)) +# else +# throw(ArgumentError("default_device should be :CPU or :GPU")) +# end +# end + +# function add_projector!(lp::PoolOfProjectors{T}, p::Proj, ::Val{:CPU}) where T <: Integer +# p = Array{T}(p) + +# if p in values(lp.data[lp.default_device]) +# key = -1 +# for guess in keys(lp.data[lp.default_device]) +# if lp.data[lp.default_device][guess] == p +# key = guess +# break +# end +# end +# else +# key = length(lp.data[lp.default_device]) + 1 +# push!(lp.data[lp.default_device], key => p) +# push!(lp.sizes, key => maximum(p)) +# end +# key +# end diff --git a/test/clustered_hamiltonian.jl b/test/clustered_hamiltonian.jl index 01381e0..476e8bf 100644 --- a/test/clustered_hamiltonian.jl +++ b/test/clustered_hamiltonian.jl @@ -88,16 +88,16 @@ end for (bd, e) in zip(bond_dimensions, edges(cl_h)) ipl, en, ipr = get_prop(cl_h, e, :ipl), get_prop(cl_h, e, :en), get_prop(cl_h, e, :ipr) - pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) - pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) + pl = get_projector!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) + pr = get_projector!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) @test minimum(size(en)) == bd end for ((i, j), cedge) ∈ cedges ipl, en, ipr = get_prop(cl_h, i, j, :ipl), get_prop(cl_h, i, j, :en), get_prop(cl_h, i, j, :ipr) - pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) - pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) + pl = get_projector!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) + pr = get_projector!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) base_i = all_states(rank[i]) base_j = all_states(rank[j]) @@ -242,8 +242,8 @@ function clustered_hamiltonian_energy(cl_h, state) for edge ∈ edges(cl_h) i, j = cl_h.reverse_label_map[src(edge)], cl_h.reverse_label_map[dst(edge)] ipl, en, ipr = get_prop(cl_h, edge, :ipl), get_prop(cl_h, edge, :en), get_prop(cl_h, edge, :ipr) - pl = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) - pr = get_projector2!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) + pl = get_projector!(get_prop(cl_h, :pool_of_projectors), ipl, :CPU) + pr = get_projector!(get_prop(cl_h, :pool_of_projectors), ipr, :CPU) edge_energy = en[pl, pr] total_en += edge_energy[state[i], state[j]] end From ea1e1d61bc44dd57149c579a1b09baa2dc82c3ac Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 20 Sep 2023 19:26:43 +0200 Subject: [PATCH 171/218] add tests on projectors --- test/projectors.jl | 53 ++++++++++++++++++++++++++++++++++++++++++++++ test/runtests.jl | 4 +++- 2 files changed, 56 insertions(+), 1 deletion(-) create mode 100644 test/projectors.jl diff --git a/test/projectors.jl b/test/projectors.jl new file mode 100644 index 0000000..bc42434 --- /dev/null +++ b/test/projectors.jl @@ -0,0 +1,53 @@ + +@testset "Add and get from pool of projectors" begin + @testset "Start with empty pool and add elements to it" begin + lp = PoolOfProjectors{Int64}() + @test length(lp) == 0 + + p1 = [1, 1, 2, 2, 3, 3] + p2 = [1, 2, 1, 3] + k = add_projector!(lp, p1) + @test k == 1 + @test length(lp) == 1 + + k = add_projector!(lp, p1) + @test k == 1 + @test length(lp) == 1 + + k = add_projector!(lp, p2) + @test k == 2 + @test length(lp) == 2 + + @test get_projector!(lp, 1) == p1 + @test get_projector!(lp, 2) == p2 + + @test length(lp, 1) == 6 + @test length(lp, 2) == 4 + @test size(lp, 1) == 3 + @test size(lp, 2) == 3 + + empty!(lp, lp.default_device) + @test length(lp) == 0 + end + + @testset "Different devices" begin + for T ∈ [Int16, Int32, Int64] + lp = PoolOfProjectors{T}() + p1 = Vector{T}([1, 1, 2, 2, 3, 3]) + p2 = Vector{T}([1, 2, 1, 3]) + k = add_projector!(lp, p1) + k = add_projector!(lp, p2) + + @test typeof(get_projector!(lp, 2, :CPU)) <: Array{T, 1} + @test typeof(get_projector!(lp, 1, :GPU)) <: CuArray{T, 1} + @test length(lp, :GPU) == 1 + @test length(lp, :CPU) == 2 + + @test typeof(get_projector!(lp, 1, :GPU)) <: CuArray{T, 1} + @test length(lp, :GPU) == 1 + + @test typeof(get_projector!(lp, 2, :GPU)) <: CuArray{T, 1} + @test length(lp, :GPU) == 2 + end + end +end diff --git a/test/runtests.jl b/test/runtests.jl index 31dc807..7d8b46c 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -5,6 +5,7 @@ using MetaGraphs using Logging using Test using TensorCast +using CUDA Base.:(==)(e1::LabelledEdge, e2::LabelledEdge) = src(e1) == src(e2) && dst(e1) == dst(e2) @@ -32,7 +33,8 @@ my_tests = [ "clustered_hamiltonian.jl", "bp_1site.jl", "bp_2site.jl", - "utils.jl" + "utils.jl", + "projectors.jl" ] for my_test ∈ my_tests From 19b1545ec1824a73a3024c77d91e88d40326a12e Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 20 Sep 2023 21:33:13 +0200 Subject: [PATCH 172/218] final cleaning projectors --- src/bp.jl | 16 +++++++++------- src/clustered_hamiltonian.jl | 6 ------ test/bp_2site.jl | 9 +++++++-- 3 files changed, 16 insertions(+), 15 deletions(-) diff --git a/src/bp.jl b/src/bp.jl index 9c23842..d415540 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -71,15 +71,13 @@ function get_neighbors(cl_h::LabelledGraph{S, T}, vertex::NTuple) where {S, T} src_node, dst_node = src(edge), dst(edge) if src_node == vertex en = get_prop(cl_h, src_node, dst_node, :en) - pv = get_prop(cl_h, src_node, dst_node, :pl) - # idx_pv = get_prop(cl_h, src_node, dst_node, :ipl) - # pv = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) + idx_pv = get_prop(cl_h, src_node, dst_node, :ipl) + pv = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) push!(neighbors, (dst_node, pv, en)) elseif dst_node == vertex en = get_prop(cl_h, src_node, dst_node, :en)' - pv = get_prop(cl_h, src_node, dst_node, :pr) - # idx_pv = get_prop(cl_h, src_node, dst_node, :ipr) - # pv = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) + idx_pv = get_prop(cl_h, src_node, dst_node, :ipr) + pv = get_projector!(get_prop(cl_h, :pool_of_projectors), idx_pv, :CPU) push!(neighbors, (src_node, pv, en)) end end @@ -150,6 +148,7 @@ function clustered_hamiltonian_2site(cl_h::LabelledGraph{S, T}, beta::Real) wher unified_vertices = unique([vertex[1:2] for vertex in vertices(cl_h)]) new_cl_h = LabelledGraph{MetaDiGraph}(unified_vertices) + new_lp = PoolOfProjectors{Int}() vertx = Set() for v in vertices(cl_h) @@ -175,9 +174,12 @@ function clustered_hamiltonian_2site(cl_h::LabelledGraph{S, T}, beta::Real) wher add_edge!(new_cl_h, (v1, v2), (w1, w2)) E, pl, pr = merge_vertices(cl_h, beta, v, w) - set_props!(new_cl_h, (v1, v2), (w1, w2), Dict(:pl => pl, :en => E, :pr => pr)) + ipl = add_projector!(new_lp, pl) + ipr = add_projector!(new_lp, pr) + set_props!(new_cl_h, (v1, v2), (w1, w2), Dict(:ipl => ipl, :en => E, :ipr => ipr)) push!(edge_states, sort([(v1, v2), (w1, w2)])) end + set_props!(new_cl_h, Dict(:pool_of_projectors => new_lp)) new_cl_h end diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index 51230b7..6591033 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -111,9 +111,6 @@ function clustered_hamiltonian( ipr = add_projector!(lp, pr) add_edge!(cl_h, v, w) - set_props!( - cl_h, v, w, Dict(:outer_edges => outer_edges, :pl => pl, :en => en, :pr => pr) - ) set_props!( cl_h, v, w, Dict(:outer_edges => outer_edges, :ipl => ipl, :en => en, :ipr => ipr) ) @@ -281,9 +278,6 @@ function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) set_props!( new_cl_h, v, w, Dict(:outer_edges => outer_edges, :ipl => ipl, :en => en, :ipr => ipr) ) - set_props!( - new_cl_h, v, w, Dict(:outer_edges => outer_edges, :pl => pl_transition, :en => en, :pr => pr_transition) - ) end set_props!(new_cl_h, Dict(:pool_of_projectors => new_lp)) diff --git a/test/bp_2site.jl b/test/bp_2site.jl index ee4962f..cea1bd6 100644 --- a/test/bp_2site.jl +++ b/test/bp_2site.jl @@ -171,8 +171,13 @@ end @test E == get_prop(cl_h1, src(e), dst(e), :en) end for e ∈ edges(new_cl_h1) - @test get_prop(new_cl_h1, src(e), dst(e), :pl) == get_prop(cl_h1, src(e), dst(e), :pl) - @test get_prop(new_cl_h1, src(e), dst(e), :pr) == get_prop(cl_h1, src(e), dst(e), :pr) + il1 = get_prop(new_cl_h1, src(e), dst(e), :ipl) + il2 = get_prop(cl_h1, src(e), dst(e), :ipl) + ir1 = get_prop(new_cl_h1, src(e), dst(e), :ipr) + ir2 = get_prop(cl_h1, src(e), dst(e), :ipr) + + @test get_projector!(get_prop(new_cl_h1, :pool_of_projectors), il1, :CPU) == get_projector!(get_prop(cl_h1, :pool_of_projectors), il2, :CPU) + @test get_projector!(get_prop(new_cl_h1, :pool_of_projectors), ir1, :CPU) == get_projector!(get_prop(cl_h1, :pool_of_projectors), ir2, :CPU) end beliefs = belief_propagation(new_cl_h1, beta; iter=iter, tol=tol) From d225be42954db8127d0d32792193144acb6d7f37 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Fri, 22 Sep 2023 12:06:03 +0200 Subject: [PATCH 173/218] add types --- src/bp.jl | 8 +++----- src/clustered_hamiltonian.jl | 4 ++-- 2 files changed, 5 insertions(+), 7 deletions(-) diff --git a/src/bp.jl b/src/bp.jl index d415540..af40d27 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -5,7 +5,7 @@ export projector -function belief_propagation(cl_h, beta; tol=1e-6, iter=1) +function belief_propagation(cl_h::LabelledGraph{S, T}, beta::Real; tol=1e-6, iter=1) where {S, T} messages_ve = Dict() messages_ev = Dict() @@ -93,7 +93,7 @@ end Base.adjoint(s::MergedEnergy) = MergedEnergy(s.e11', s.e21', s.e12', s.e22') -function update_message( E_bond::AbstractArray, message::Vector, beta::Real) +function update_message(E_bond::AbstractArray, message::Vector, beta::Real) E_bond = E_bond .- minimum(E_bond) exp.(-beta * E_bond) * message end @@ -246,9 +246,7 @@ function projector(cl_h::LabelledGraph{S, T}, v::NTuple{N, Int64}, w::NTuple{N, end end -function fuse_projectors( - projectors::NTuple{N, K} - ) where {N, K} +function fuse_projectors(projectors::NTuple{N, K}) where {N, K} fused, transitions_matrix = rank_reveal(hcat(projectors...), :PE) transitions = Tuple(Array(t) for t ∈ eachcol(transitions_matrix)) fused, transitions diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index ed418d0..c97bc66 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -86,7 +86,7 @@ function clustered_hamiltonian(ig::IsingGraph; spectrum::Function=full_spectrum, clustered_hamiltonian(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end -function rank_reveal(energy, order=:PE) where T <: Real +function rank_reveal(energy, order=:PE) where T <: Real #TODO: add type @assert order ∈ (:PE, :EP) dim = order == :PE ? 1 : 2 E, idx = unique_dims(energy, dim) @@ -99,7 +99,7 @@ Returns Dict(vertex of ising graph -> spin value) Assumes that state has the same order as vertices in factor graph! TODO: check the order consistency over external packages. """ -function decode_clustered_hamiltonian_state(cl_h, state::Vector{Int}) +function decode_clustered_hamiltonian_state(cl_h::LabelledGraph{S, T}, state::Vector{Int}) where {S, T} ret = Dict{Int, Int}() for (i, vert) ∈ zip(state, vertices(cl_h)) spins = get_prop(cl_h, vert, :cluster).labels From 12877c3648a7bec2a147b975bc68faa3f8e4e3f7 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Sat, 23 Sep 2023 13:54:33 +0200 Subject: [PATCH 174/218] splitting overly long lines --- src/clustered_hamiltonian.jl | 16 +++++++-- src/projectors.jl | 64 ++++------------------------------- src/truncate.jl | 24 +++++++++---- test/bp_2site.jl | 8 +++-- test/clustered_hamiltonian.jl | 2 +- 5 files changed, 44 insertions(+), 70 deletions(-) diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index c97bc66..6b761de 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -82,7 +82,11 @@ function clustered_hamiltonian( cl_h end -function clustered_hamiltonian(ig::IsingGraph; spectrum::Function=full_spectrum, cluster_assignment_rule::Dict{Int, T}) where T +function clustered_hamiltonian( + ig::IsingGraph; + spectrum::Function=full_spectrum, + cluster_assignment_rule::Dict{Int, T} + ) where T clustered_hamiltonian(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end @@ -150,7 +154,12 @@ function energy_2site(cl_h::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} int_eng end -function bond_energy(cl_h::LabelledGraph{S, T}, cl_h_u::NTuple{N, Int64}, cl_h_v::NTuple{N, Int64}, σ::Int) where {S, T, N} +function bond_energy( + cl_h::LabelledGraph{S, T}, + cl_h_u::NTuple{N, Int64}, + cl_h_v::NTuple{N, Int64}, + σ::Int + ) where {S, T, N} if has_edge(cl_h, cl_h_u, cl_h_v) ipu, en, ipv = get_prop.( Ref(cl_h), Ref(cl_h_u), Ref(cl_h_v), (:ipl, :en, :ipr) @@ -174,7 +183,8 @@ function cluster_size(clustered_hamiltonian::LabelledGraph{S, T}, vertex::T) whe length(get_prop(clustered_hamiltonian, vertex, :spectrum).energies) end -function exact_cond_prob(clustered_hamiltonian::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors +function exact_cond_prob(clustered_hamiltonian::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} + # TODO: Not going to work without PoolOfProjectors ver = vertices(clustered_hamiltonian) rank = cluster_size.(Ref(clustered_hamiltonian), ver) states = [Dict(ver .=> σ) for σ ∈ Iterators.product([1:r for r ∈ rank]...)] diff --git a/src/projectors.jl b/src/projectors.jl index 53a80d0..56a6ef7 100644 --- a/src/projectors.jl +++ b/src/projectors.jl @@ -10,9 +10,11 @@ struct PoolOfProjectors{T <: Integer} default_device::Symbol sizes::Dict{Int, Int} - PoolOfProjectors(data::Dict{Int, Dict{Int, Vector{T}}}) where T = new{T}(Dict(:CPU => data), - :CPU, - Dict{Int, Int}(k => maximum(v) for (k, v) ∈ data)) + PoolOfProjectors( + data::Dict{Int, Dict{Int, Vector{T}}} + ) where T = new{T}(Dict(:CPU => data), + :CPU, + Dict{Int, Int}(k => maximum(v) for (k, v) ∈ data)) PoolOfProjectors{T}() where T = new{T}(Dict(:CPU => Dict{Int, Proj{T}}()), :CPU, Dict{Int, Int}()) @@ -75,58 +77,4 @@ function add_projector!(lp::PoolOfProjectors{T}, p::Proj) where T <: Integer push!(lp.sizes, key => maximum(p)) end key -end - -# get_projector!(lp::PoolOfProjectors, index::Int) = get_projector!(lp, index, lp.default_device) - -# # TODO This is version for only one GPU -# function get_projector!(lp::PoolOfProjectors{T}, index::Int, ::Val{:CPU}) where T <: Integer -# device = :CPU -# if device ∉ keys(lp.data) -# push!(lp.data, device => Dict{Int, Proj{T}}()) -# end - -# if index ∉ keys(lp.data[device]) -# if device == :GPU -# p = CuArray{T}(lp.data[lp.default_device][index]) -# elseif device == :CPU -# p = Array{T}(lp.data[lp.default_device][index]) -# else -# throw(ArgumentError("device should be :CPU or :GPU")) -# end -# push!(lp.data[device], index => p) -# end -# lp.data[device][index] -# end - - -# add_projector!(lp::PoolOfProjectors, p::Proj) = add_projector!(lp::PoolOfProjectors, p::Proj, lp.default_device) - -# function add_projector!(lp::PoolOfProjectors{T}, p::Proj, device::Symbol) where T <: Integer -# if device == :CPU -# return add_projector!(lp::PoolOfProjectors, p::Proj, Val(device)) -# elseif device == :GPU -# return SpinGlassTensors.add_projector!(lp::PoolOfProjectors, p::Proj, Val(device)) -# else -# throw(ArgumentError("default_device should be :CPU or :GPU")) -# end -# end - -# function add_projector!(lp::PoolOfProjectors{T}, p::Proj, ::Val{:CPU}) where T <: Integer -# p = Array{T}(p) - -# if p in values(lp.data[lp.default_device]) -# key = -1 -# for guess in keys(lp.data[lp.default_device]) -# if lp.data[lp.default_device][guess] == p -# key = guess -# break -# end -# end -# else -# key = length(lp.data[lp.default_device]) + 1 -# push!(lp.data[lp.default_device], key => p) -# push!(lp.sizes, key => maximum(p)) -# end -# key -# end +end \ No newline at end of file diff --git a/src/truncate.jl b/src/truncate.jl index 42ecfd2..4107720 100644 --- a/src/truncate.jl +++ b/src/truncate.jl @@ -4,7 +4,13 @@ export truncate_clustered_hamiltonian_2site_BP -function truncate_clustered_hamiltonian_1site_BP(cl_h::LabelledGraph{S, T}, num_states::Int; beta=1.0, tol=1e-10, iter=1) where {S, T} +function truncate_clustered_hamiltonian_1site_BP( + cl_h::LabelledGraph{S, T}, + num_states::Int; + beta=1.0, + tol=1e-10, + iter=1 + ) where {S, T} states = Dict() beliefs = belief_propagation(cl_h, beta; tol=tol, iter=iter) for node in vertices(cl_h) @@ -14,7 +20,8 @@ function truncate_clustered_hamiltonian_1site_BP(cl_h::LabelledGraph{S, T}, num_ truncate_clustered_hamiltonian(cl_h, states) end -function truncate_clustered_hamiltonian_2site_energy(cl_h::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 +function truncate_clustered_hamiltonian_2site_energy(cl_h::LabelledGraph{S, T}, num_states::Int) where {S, T} + # TODO: name to be clean to make it consistent with square2 and squarestar2 states = Dict() for node in vertices(cl_h) if node in keys(states) continue end @@ -31,9 +38,13 @@ function truncate_clustered_hamiltonian_2site_energy(cl_h::LabelledGraph{S, T}, truncate_clustered_hamiltonian(cl_h, states) end -function truncate_clustered_hamiltonian_2site_BP(cl_h::LabelledGraph{S, T}, beliefs::Dict, num_states::Int; beta=1.0) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 - # new_cl_h = clustered_hamiltonian_2site(cl_h, beta) - # beliefs = belief_propagation(new_cl_h, beta; tol, iter) +function truncate_clustered_hamiltonian_2site_BP( + cl_h::LabelledGraph{S, T}, + beliefs::Dict, + num_states::Int; + beta=1.0 + ) where {S, T} + # TODO: name to be clean to make it consistent with square2 and squarestar2 states = Dict() for node in vertices(cl_h) if node in keys(states) continue end @@ -49,7 +60,8 @@ end function select_numstate_best(E, sx, num_states) # truncate based on energy in two nodes of factor graph; - # resulting states are a product of states in two nodes, so we have to fine-tune to end up with expected number of states + # resulting states are a product of states in two nodes, + # so we have to fine-tune to end up with expected number of states low, high = 1, min(num_states, length(E)) diff --git a/test/bp_2site.jl b/test/bp_2site.jl index cea1bd6..c49f7d3 100644 --- a/test/bp_2site.jl +++ b/test/bp_2site.jl @@ -176,8 +176,12 @@ end ir1 = get_prop(new_cl_h1, src(e), dst(e), :ipr) ir2 = get_prop(cl_h1, src(e), dst(e), :ipr) - @test get_projector!(get_prop(new_cl_h1, :pool_of_projectors), il1, :CPU) == get_projector!(get_prop(cl_h1, :pool_of_projectors), il2, :CPU) - @test get_projector!(get_prop(new_cl_h1, :pool_of_projectors), ir1, :CPU) == get_projector!(get_prop(cl_h1, :pool_of_projectors), ir2, :CPU) + pl1 = get_projector!(get_prop(new_cl_h1, :pool_of_projectors), il1, :CPU) + pl2 = get_projector!(get_prop(cl_h1, :pool_of_projectors), il2, :CPU) + pr1 = get_projector!(get_prop(new_cl_h1, :pool_of_projectors), ir1, :CPU) + pr2 = get_projector!(get_prop(cl_h1, :pool_of_projectors), ir2, :CPU) + @test pl1 == pl2 + @test pr1 == pr2 end beliefs = belief_propagation(new_cl_h1, beta; iter=iter, tol=tol) diff --git a/test/clustered_hamiltonian.jl b/test/clustered_hamiltonian.jl index 9e1fa8d..cc902c2 100644 --- a/test/clustered_hamiltonian.jl +++ b/test/clustered_hamiltonian.jl @@ -15,7 +15,7 @@ enum(vec) = Dict(v => i for (i, v) ∈ enumerate(vec)) for T ∈ [Float16, Float32, Float64] ig = ising_graph(T, instance) - cl_h = clustered_hamiltonian(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t)) ) + cl_h = clustered_hamiltonian(ig, 2, cluster_assignment_rule=super_square_lattice((m, n, 2*t))) @test collect(vertices(cl_h)) == [(i, j) for i ∈ 1:m for j ∈ 1:n] From e46d1bcd2b226312bebf6f0ce03a0307735ed5ea Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Mon, 25 Sep 2023 10:34:23 +0200 Subject: [PATCH 175/218] exception in states_int --- src/clustered_hamiltonian.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index 6b761de..41dac2c 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -203,7 +203,7 @@ function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) cl = get_prop(cl_h, v, :cluster) sp = get_prop(cl_h, v, :spectrum) if sp.states == Vector{Int64}[] - sp = Spectrum(sp.energies[states[v]], sp.states, []) + sp = Spectrum(sp.energies[states[v]], sp.states, [1,]) else sp = Spectrum(sp.energies[states[v]], sp.states[states[v]]) end From 14467900af6c7a7d5e8e0b96078a2c50575aadda Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 27 Sep 2023 12:03:02 +0200 Subject: [PATCH 176/218] add docs --- docs/make.jl | 21 +++++++++++++++++++++ docs/src/api.md | 25 +++++++++++++++++++++++++ docs/src/index.md | 6 ++++++ docs/src/userguide.md | 42 ++++++++++++++++++++++++++++++++++++++++++ 4 files changed, 94 insertions(+) create mode 100644 docs/make.jl create mode 100644 docs/src/api.md create mode 100644 docs/src/index.md create mode 100644 docs/src/userguide.md diff --git a/docs/make.jl b/docs/make.jl new file mode 100644 index 0000000..fbb6101 --- /dev/null +++ b/docs/make.jl @@ -0,0 +1,21 @@ +using Documenter, SpinGlassNetworks + +_pages = [ + "Introduction" => "index.md", + "User guide" => "userguide.md", + "API Reference" => "api.md" +] + +# ============================ +format = Documenter.HTML(edit_link = "master", + prettyurls = get(ENV, "CI", nothing) == "true", +) + +# format = Documenter.LaTeX(platform="none") + +makedocs( + sitename="SpinGlassNetworks.jl", + modules = [SpinGlassNetworks], + pages = _pages, + format = format + ) \ No newline at end of file diff --git a/docs/src/api.md b/docs/src/api.md new file mode 100644 index 0000000..228e417 --- /dev/null +++ b/docs/src/api.md @@ -0,0 +1,25 @@ +# Library + +--- + +```@meta +CurrentModule = SpinGlassNetworks +``` + +## Ising Graphs + +```@docs + +``` + +## Factor Graphs + +```@docs + +``` + +## Auxiliary Functions + +```@docs + +``` \ No newline at end of file diff --git a/docs/src/index.md b/docs/src/index.md new file mode 100644 index 0000000..7fd6448 --- /dev/null +++ b/docs/src/index.md @@ -0,0 +1,6 @@ +# SpinGlassNetworks + +A [Julia](http://julialang.org) package for building and interacting with Ising spin glass models in context of tensor networks. Part of [SpinGlassPEPS](https://github.com/euro-hpc-pl/SpinGlassPEPS.jl) package. + + + diff --git a/docs/src/userguide.md b/docs/src/userguide.md new file mode 100644 index 0000000..184c127 --- /dev/null +++ b/docs/src/userguide.md @@ -0,0 +1,42 @@ +# Introduction +This section provides examples of how to use the 'ising_graph' function to generate an Ising model graph and the 'factor_graph' function to convert the Ising graph into a factor graph. + +# Ising Graph +The Ising model is a mathematical model used to describe the behavior of interacting particles, such as atoms or molecules, in a magnetic field. In the Ising model, each particle is represented as a binary variable $s_i$ that can take on the values of either +1 or -1. The total energy of the system is given by the Hamiltonian: + +$$H = \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$$ + +where $J_{ij}$ is the coupling constant between particles $i$ and $j$, $h_i$ is the external magnetic field at particle $i$, and the sum is taken over all pairs of particles and all particles in the system $\mathcal{E}$, respectively. + + +## simple examle + + +## Generalisation + +The 'ising_graph' function is quite general function. One can easly convert instance into another hamiltonian convention, ex. +```math +H = - \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j - \mu \sum_{i} h_i s_i +``` +This conversion is directed by `sgn` parameter of `ising_graph`. It is wort doing, because then all `energy` functions will work as one intended. + + +'ising_graph' also allows for building other spin system, not only spin-``\frac{1}{2}`` system. For example one may build chain where sites allows for 3 spin values. + + + +# factor graph + +A factor graph is a graphical representation that allows for a convenient and intuitive way to describe the structure of a tensor network. + +A factor graph consists of two types of nodes: variable nodes and factor nodes. Variable nodes represent the tensors in the tensor network, and factor nodes represent the operations that are applied to those tensors. + +Each variable node in the factor graph corresponds to a tensor in the tensor network, and each factor node corresponds to a tensor contraction or operation that is applied to one or more of those tensors. The edges between the nodes in the factor graph represent the indices that are shared between the corresponding tensors in the tensor network. + +## Simple example + + + +## Chimera graphs +The Chimera graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. It is a two-dimensional lattice of unit cells, each consisting of a bipartite graph of $K_{4,4}$ complete bipartite subgraphs. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#chimera-graph). + From 69fedcf00d42479c7cfe5c5db45a762b13ef8889 Mon Sep 17 00:00:00 2001 From: annamariadziubyna <73058800+annamariadziubyna@users.noreply.github.com> Date: Thu, 28 Sep 2023 20:06:27 +0200 Subject: [PATCH 177/218] docs --- docs/src/api.md | 15 +++--- docs/src/userguide.md | 103 ++++++++++++++++++++++++++++++++++++++---- 2 files changed, 101 insertions(+), 17 deletions(-) diff --git a/docs/src/api.md b/docs/src/api.md index 228e417..ec7999f 100644 --- a/docs/src/api.md +++ b/docs/src/api.md @@ -7,19 +7,20 @@ CurrentModule = SpinGlassNetworks ``` ## Ising Graphs - ```@docs - +ising_graph +inter_cluster_edges +prune ``` -## Factor Graphs - +## Clustered Hamiltonian ```@docs - +split_into_clusters +clustered_hamiltonian +decode_clustered_hamiltonian_state ``` ## Auxiliary Functions - ```@docs - +zephyr_to_linear ``` \ No newline at end of file diff --git a/docs/src/userguide.md b/docs/src/userguide.md index 184c127..69c8b84 100644 --- a/docs/src/userguide.md +++ b/docs/src/userguide.md @@ -1,5 +1,5 @@ # Introduction -This section provides examples of how to use the 'ising_graph' function to generate an Ising model graph and the 'factor_graph' function to convert the Ising graph into a factor graph. +This section provides examples of how to use the 'ising_graph' function to generate an Ising model graph and the 'clustered_hamiltonian' function to convert the Ising graph into a clustered Hamiltonian. # Ising Graph The Ising model is a mathematical model used to describe the behavior of interacting particles, such as atoms or molecules, in a magnetic field. In the Ising model, each particle is represented as a binary variable $s_i$ that can take on the values of either +1 or -1. The total energy of the system is given by the Hamiltonian: @@ -9,8 +9,19 @@ $$H = \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$$ where $J_{ij}$ is the coupling constant between particles $i$ and $j$, $h_i$ is the external magnetic field at particle $i$, and the sum is taken over all pairs of particles and all particles in the system $\mathcal{E}$, respectively. -## simple examle +## Simple example +```@example +using SpinGlassNetworks +# Create Ising instance +instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, +(1, 2) => -1.0, (2, 3) => 1.0) + +# Generate Ising graph +ig = ising_graph(instance) +# View graph properties +@show biases(ig), couplings(ig) +``` ## Generalisation @@ -18,25 +29,97 @@ The 'ising_graph' function is quite general function. One can easly convert inst ```math H = - \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j - \mu \sum_{i} h_i s_i ``` -This conversion is directed by `sgn` parameter of `ising_graph`. It is wort doing, because then all `energy` functions will work as one intended. - 'ising_graph' also allows for building other spin system, not only spin-``\frac{1}{2}`` system. For example one may build chain where sites allows for 3 spin values. +```@example +using SpinGlassNetworks + +# Create spin chain instance +instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, +(1, 2) => -1.0, (2, 3) => 1.0) + +rank_override = Dict(1 => 3, 2 => 3, 3 => 3) +sg = ising_graph(instance, rank_override=rank_override) -# factor graph +# see ranks of each site +rank_vec(sg) +``` + +# Clustered Hamiltonian -A factor graph is a graphical representation that allows for a convenient and intuitive way to describe the structure of a tensor network. +A clustered Hamiltonian is a graphical representation that allows for a convenient and intuitive way to describe the structure of a tensor network. -A factor graph consists of two types of nodes: variable nodes and factor nodes. Variable nodes represent the tensors in the tensor network, and factor nodes represent the operations that are applied to those tensors. +A clustered Hamiltonian consists of two types of nodes: variable nodes and factor nodes. Variable nodes represent the tensors in the tensor network, and factor nodes represent the operations that are applied to those tensors. -Each variable node in the factor graph corresponds to a tensor in the tensor network, and each factor node corresponds to a tensor contraction or operation that is applied to one or more of those tensors. The edges between the nodes in the factor graph represent the indices that are shared between the corresponding tensors in the tensor network. +Each variable node in the clustered Hamiltonian corresponds to a tensor in the tensor network, and each factor node corresponds to a tensor contraction or operation that is applied to one or more of those tensors. The edges between the nodes in the clustered Hamiltonian represent the indices that are shared between the corresponding tensors in the tensor network. ## Simple example +```@example +using SpinGlassNetworks + +# Prepare simple instance +instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, +(1, 2) => -1.0, (2, 3) => 1.0) +ig = ising_graph(instance) + +# Create factor graph. +cl_h = clustered_hamiltonian( + ig, + cluster_assignment_rule = super_square_lattice((3, 1, 1)) +) +``` + +## Pegasus graphs +The Pegasus graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. It is a two-dimensional lattice of unit cells, each consisting of a bipartite graph of $K_{4,4}$ complete bipartite subgraphs. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#pegasus-graph). +```@raw html + +``` + +```@example +using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs + +# load Chimera instance and create Ising graph +instance = "$(@__DIR__)/../../src/instances/pegasus_random/P4/RAU/001_sg.txt" +ig = ising_graph(instance) + +# Loaded instance is pegasus graph +m = 3 +n = 3 +t = 3 + +cl_h = clustered_hamiltonian( + ig, + cluster_assignment_rule = pegasus_lattice((m, n, t)) +) + +println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in factor graph: ", length(LabelledGraphs.vertices(cl_h))) +``` + + +## Zephyr graphs +The Zephyr graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#zephyr-graph). +```@raw html + +``` +```@example +using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs + +# load Chimera instance and create Ising graph +instance = "$(@__DIR__)/../../src/instances/zephyr_random/Z3/RAU/001_sg.txt" +ig = ising_graph(instance) +# Loaded instance is zephyr graph +m = 6 +n = 6 +t = 4 -## Chimera graphs -The Chimera graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. It is a two-dimensional lattice of unit cells, each consisting of a bipartite graph of $K_{4,4}$ complete bipartite subgraphs. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#chimera-graph). +cl_h = clustered_hamiltonian( + ig, + cluster_assignment_rule = zephyr_lattice((m, n, t)) +) +println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in factor graph: ", length(LabelledGraphs.vertices(cl_h))) +``` \ No newline at end of file From 1614f468f91a0bb330538dab2f17de52e062ec4b Mon Sep 17 00:00:00 2001 From: annamariadziubyna <73058800+annamariadziubyna@users.noreply.github.com> Date: Mon, 2 Oct 2023 21:24:27 +0200 Subject: [PATCH 178/218] add docstrings --- docs/src/api.md | 53 ++++++++++ docs/src/userguide.md | 2 +- src/bp.jl | 178 +++++++++++++++++++++++++++++-- src/clustered_hamiltonian.jl | 200 +++++++++++++++++++++++++++++++++-- src/ising.jl | 60 ++++++++++- src/lattice.jl | 54 +++++++++- src/projectors.jl | 52 ++++++++- src/spectrum.jl | 89 +++++++++++++++- src/truncate.jl | 63 ++++++++++- 9 files changed, 722 insertions(+), 29 deletions(-) diff --git a/docs/src/api.md b/docs/src/api.md index ec7999f..3e134c7 100644 --- a/docs/src/api.md +++ b/docs/src/api.md @@ -11,6 +11,7 @@ CurrentModule = SpinGlassNetworks ising_graph inter_cluster_edges prune +couplings ``` ## Clustered Hamiltonian @@ -18,6 +19,58 @@ prune split_into_clusters clustered_hamiltonian decode_clustered_hamiltonian_state +rank_reveal +energy +energy_2site +cluster_size +bond_energy +exact_cond_prob +truncate_clustered_hamiltonian +``` + +## Lattice +```@docs +super_square_lattice +pegasus_lattice +zephyr_lattice +``` + +## Belief propagation +```@docs +local_energy +interaction_energy +get_neighbors +belief_propagation +MergedEnergy +update_message +clustered_hamiltonian_2site +merge_vertices_cl_h +projector +SparseCSC +``` + +## Projectors +```@docs +PoolOfProjectors +get_projector! +add_projector! +empty! +``` + +## Spectrum +```@docs +Spectrum +matrix_to_integers +gibbs_tensor +brute_force +``` + +## Truncate +```@docs +truncate_clustered_hamiltonian_1site_BP +truncate_clustered_hamiltonian_2site_BP +truncate_clustered_hamiltonian_2site_energy +select_numstate_best ``` ## Auxiliary Functions diff --git a/docs/src/userguide.md b/docs/src/userguide.md index 69c8b84..f31cca2 100644 --- a/docs/src/userguide.md +++ b/docs/src/userguide.md @@ -73,7 +73,7 @@ cl_h = clustered_hamiltonian( ``` ## Pegasus graphs -The Pegasus graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. It is a two-dimensional lattice of unit cells, each consisting of a bipartite graph of $K_{4,4}$ complete bipartite subgraphs. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#pegasus-graph). +The Pegasus graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. It is designed to provide a grid of qubits with specific connectivity patterns optimized for solving certain optimization problems. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#pegasus-graph). ```@raw html ``` diff --git a/src/bp.jl b/src/bp.jl index af40d27..f9ddb34 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -2,9 +2,32 @@ export belief_propagation, clustered_hamiltonian_2site, - projector - - + projector, + get_neighbors, + MergedEnergy, + update_message, + merge_vertices_cl_h, + local_energy, + interaction_energy, + SparseCSC + +""" +Perform belief propagation on a given clustered hamiltonian. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered hamiltonian represented as a labeled graph. +- `beta::Real`: The temperature parameter for the belief propagation algorithm. +- `tol::Real (optional, default=1e-6)`: The convergence tolerance. The algorithm stops when the message updates between iterations are smaller than this value. +- `iter::Int (optional, default=1)`: The maximum number of iterations to perform. + +# Returns: +- `beliefs::Dict`: A dictionary where keys are vertices of clustered hamiltonian, and values are the resulting beliefs after belief propagation. + +The function implements belief propagation on the given clustered hamiltonian `cl_h` to calculate beliefs for each vertex. +Belief propagation is an iterative algorithm that computes beliefs by passing messages between vertices and edges of the clustered hamiltonian. +The algorithm continues until convergence or until the specified maximum number of iterations is reached. +The beliefs are computed based on the temperature parameter `beta`, which controls the influence of energy values on the beliefs. +""" function belief_propagation(cl_h::LabelledGraph{S, T}, beta::Real; tol=1e-6, iter=1) where {S, T} messages_ve = Dict() messages_ev = Dict() @@ -65,6 +88,21 @@ function belief_propagation(cl_h::LabelledGraph{S, T}, beta::Real; tol=1e-6, ite beliefs end +""" +Returns the neighbors of a given vertex in a clustered Hamiltonian. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `vertex::NTuple`: The vertex for which neighbors are to be retrieved. + +# Returns: +- `neighbors::Vector{Tuple}`: A vector of tuples representing the neighbors of the specified vertex. Each tuple contains the following information: + - `dst_node::T`: The neighboring vertex. + - `pv::Matrix`: The projector associated with the edge connecting the vertex and its neighbor. + - `en::Real`: The energy associated with the edge connecting the vertex and its neighbor. + +This function retrieves the neighbors of a given vertex in a clustered Hamiltonian graph. It iterates through the edges of the graph and identifies edges connected to the specified vertex. For each neighboring edge, it extracts and returns the neighboring vertex, the associated projector, and the energy. +""" function get_neighbors(cl_h::LabelledGraph{S, T}, vertex::NTuple) where {S, T} neighbors = [] for edge in edges(cl_h) @@ -84,6 +122,19 @@ function get_neighbors(cl_h::LabelledGraph{S, T}, vertex::NTuple) where {S, T} return neighbors end +""" +A custom Julia struct representing energy values in a merged format for use in specific calculations. + +# Fields: +- `e11::AbstractMatrix{T}` +- `e12::AbstractMatrix{T}` +- `e21::AbstractMatrix{T}` +- `e22::AbstractMatrix{T}` + +The `MergedEnergy` struct is used to represent energy values that are organized in a merged format. This format is often utilized in certain computational tasks, where energy values are categorized based on combinations of left and right factors. + +Each field of the `MergedEnergy` struct stores energy values as an `AbstractMatrix{T}` of type `T`, where `T` is a subtype of the `Real` abstract type. The specific organization and interpretation of these energy values depend on the context in which this struct is used. +""" struct MergedEnergy{T <: Real} e11::AbstractMatrix{T} e12::AbstractMatrix{T} @@ -93,11 +144,41 @@ end Base.adjoint(s::MergedEnergy) = MergedEnergy(s.e11', s.e21', s.e12', s.e22') +""" +Update a message using energy values and temperature. + +# Arguments: +- `E_bond::AbstractArray`: An array of energy values associated with a bond or interaction. +- `message::Vector`: The input message vector to be updated. +- `beta::Real`: The temperature parameter controlling the influence of energy values. + +# Returns: +- `updated_message::Vector`: The updated message vector after applying the energy-based update. + +This function takes energy values `E_bond` associated with a bond or interaction, an input message vector `message`, and a temperature parameter `beta`. It updates the message by first adjusting the energy values relative to their minimum value, exponentiating them with a negative sign and scaling by `beta`, and then multiplying them element-wise with the input message. + +The result is an updated message that reflects the influence of energy values and temperature. +""" function update_message(E_bond::AbstractArray, message::Vector, beta::Real) E_bond = E_bond .- minimum(E_bond) exp.(-beta * E_bond) * message end +""" +Update a message using energy values and temperature in a merged energy format. + +# Arguments: +- `E_bond::MergedEnergy`: An instance of the `MergedEnergy` type representing energy values for the bond or interaction. +- `message::Vector`: The input message vector to be updated. +- `beta::Real`: The temperature parameter controlling the influence of energy values. + +# Returns: +- `updated_message::Vector`: The updated message vector after applying the energy-based update. + +This function takes energy values `E_bond` in a merged energy format, an input message vector `message`, and a temperature parameter `beta`. It updates the message based on the energy values and temperature using a specified algorithm. + +The `MergedEnergy` type represents energy values in a merged format, and the function processes these values accordingly to update the message vector. +""" function update_message(E_bond::MergedEnergy, message::Vector, beta::Real) e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 # equivalent to @@ -143,7 +224,20 @@ function update_message(E_bond::MergedEnergy, message::Vector, beta::Real) R end - +""" +Constructs a clustered Hamiltonian for a given clustered Hamiltonian with a 2-site cluster approximation. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `beta::Real`: The temperature parameter for the 2-site cluster Hamiltonian construction. + +# Returns: +- `new_cl_h::LabelledGraph{MetaDiGraph}`: A new labeled graph representing the 2-site cluster Hamiltonian. + + This function constructs a clustered Hamiltonian `cl_h` by applying a 2-site cluster approximation. It combines and merges vertices and edges of the original graph to create a simplified representation of the Hamiltonian. + +The resulting `new_cl_h` graph represents the 2-site cluster Hamiltonian with simplified interactions between clusters. The energy values, projectors, and spectra associated with the new vertices and edges are computed based on the provided temperature parameter `beta`. +""" function clustered_hamiltonian_2site(cl_h::LabelledGraph{S, T}, beta::Real) where {S, T} unified_vertices = unique([vertex[1:2] for vertex in vertices(cl_h)]) @@ -173,7 +267,7 @@ function clustered_hamiltonian_2site(cl_h::LabelledGraph{S, T}, beta::Real) wher add_edge!(new_cl_h, (v1, v2), (w1, w2)) - E, pl, pr = merge_vertices(cl_h, beta, v, w) + E, pl, pr = merge_vertices_cl_h(cl_h, beta, v, w) ipl = add_projector!(new_lp, pl) ipr = add_projector!(new_lp, pr) set_props!(new_cl_h, (v1, v2), (w1, w2), Dict(:ipl => ipl, :en => E, :ipr => ipr)) @@ -183,7 +277,25 @@ function clustered_hamiltonian_2site(cl_h::LabelledGraph{S, T}, beta::Real) wher new_cl_h end -function merge_vertices(cl_h::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int64}, node2::NTuple{3, Int64} +""" +Merge two vertices in a clustered Hamiltonian to create a single merged vertex. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `β::Real`: The temperature parameter controlling the influence of energy values. +- `node1::NTuple{3, Int64}`: The coordinates of the first vertex to merge. +- `node2::NTuple{3, Int64}`: The coordinates of the second vertex to merge. + +# Returns: +- `merged_energy::MergedEnergy`: An instance of the `MergedEnergy` type representing the merged energy values. +- `pl::AbstractVector`: The merged left projector. +- `pr::AbstractVector`: The merged right projector. + +This function merges two vertices in a clustered Hamiltonian graph `cl_h` to create a single merged vertex. The merging process combines projectors and energy values associated with the original vertices based on the provided temperature parameter `β`. + +The merged energy values, left projector `pl`, and right projector `pr` are computed based on the interactions between the original vertices and their respective projectors. +""" +function merge_vertices_cl_h(cl_h::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int64}, node2::NTuple{3, Int64} ) where {S, T} i1, j1, _ = node1 i2, j2, _ = node2 @@ -220,10 +332,38 @@ function merge_vertices(cl_h::LabelledGraph{S, T}, β::Real, node1::NTuple{3, In MergedEnergy(e11, e12, e21, e22), pl, pr end +""" +Get the local energy associated with a vertex in a clustered Hamiltonian. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `v::NTuple{3, Int64}`: The coordinates of the vertex for which the local energy is requested. + +# Returns: +- `local_energy::AbstractVector`: An abstract vector containing the local energy values associated with the specified vertex. + +This function retrieves the local energy values associated with a given vertex `v` in a clustered Hamiltonian graph `cl_h`. If the vertex exists in the graph and has associated energy values, it returns those values; otherwise, it returns a vector of zeros. + +The local energy values are typically obtained from the spectrum associated with the vertex. +""" function local_energy(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}) where {S, T} has_vertex(cl_h, v) ? get_prop(cl_h, v, :spectrum).energies : zeros(1) end +""" +Get the interaction energy between two vertices in a clustered Hamiltonian. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `v::NTuple{3, Int64}`: The coordinates of the first vertex. +- `w::NTuple{3, Int64}`: The coordinates of the second vertex. + +# Returns: +- `interaction_energy::AbstractMatrix`: An abstract matrix containing the interaction energy values between the specified vertices. + +This function retrieves the interaction energy values between two vertices, `v` and `w`, in a clustered Hamiltonian graph `cl_h`. If there is a directed edge from `w` to `v`, it returns the corresponding energy values; if there is a directed edge from `v` to `w`, it returns the transpose of the energy values; otherwise, it returns a matrix of zeros. +The interaction energy values represent the energy associated with the interaction or connection between the two vertices. +""" function interaction_energy(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} if has_edge(cl_h, w, v) get_prop(cl_h, w, v, :en)' @@ -234,6 +374,19 @@ function interaction_energy(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::N end end +""" +Get the projector associated with an edge between two vertices in a clustered Hamiltonian. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `v::NTuple{N, Int64}`: The coordinates of one of the two vertices connected by the edge. +- `w::NTuple{N, Int64}`: The coordinates of the other vertex connected by the edge. + +# Returns: +- `p::AbstractVector`: An abstract vector representing the projector associated with the specified edge. + +This function retrieves the projector associated with an edge between two vertices, `v` and `w`, in a clustered Hamiltonian graph `cl_h`. If there is a directed edge from `w` to `v`, it returns the index of right projector (`:ipr`); if there is a directed edge from `v` to `w`, it returns the index of left projector (`:ipl`). If no edge exists between the vertices, it returns a vector of ones. +""" function projector(cl_h::LabelledGraph{S, T}, v::NTuple{N, Int64}, w::NTuple{N, Int64}) where {S, T, N} if has_edge(cl_h, w, v) idx_p = get_prop(cl_h, w, v, :ipr) @@ -256,6 +409,19 @@ function outer_projector(p1::Array{T, 1}, p2::Array{T, 1}) where T <: Number reshape(reshape(p1, :, 1) .+ maximum(p1) .* reshape(p2 .- 1, 1, :), :) end +""" +Create a sparse column-compressed (CSC) matrix with specified column indices and values. + +# Arguments: +- `::Type{R}`: The element type of the sparse matrix (e.g., `Float64`, `Int64`). +- `p::Vector{Int64}`: A vector of column indices for the non-zero values. + +# Returns: +- `sparse_matrix::SparseMatrixCSC{R}`: A sparse column-compressed matrix with non-zero values at specified columns. + +This constructor function creates a sparse column-compressed (CSC) matrix of element type `R` based on the provided column indices `p` and values. The resulting matrix has non-zero values at the specified column indices, while all other elements are zero. +The `SparseCSC` constructor is useful for creating sparse matrices with specific column indices and values efficiently. +""" function SparseCSC(::Type{R}, p::Vector{Int64}) where R <: Real n = length(p) mp = maximum(p) diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index 41dac2c..ad0b220 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -8,12 +8,25 @@ export cluster_size, truncate_clustered_hamiltonian, exact_cond_prob, - bond_energy + bond_energy, + cluster_size """ -Groups spins into clusters: Dict(factor graph coordinates -> group of spins in Ising graph) -""" +Group spins into clusters based on an assignment rule, mapping factor graph coordinates to groups of spins in the Ising graph. +Dict(factor graph coordinates -> group of spins in Ising graph) + +# Arguments: +- `ig::LabelledGraph{G, L}`: The Ising graph represented as a labeled graph. +- `assignment_rule`: A mapping that assigns Ising graph vertices to clusters based on factor graph coordinates. + +# Returns: +- `clusters::Dict{L, Vertex}`: A dictionary mapping cluster identifiers to representative vertices in the Ising graph. + +This function groups spins in the Ising graph into clusters based on an assignment rule. The assignment rule defines how factor graph coordinates correspond to clusters of spins in the Ising graph. Each cluster is represented by a vertex from the Ising graph. + +The `split_into_clusters` function is useful for organizing and analyzing spins in complex spin systems, particularly in the context of clustered Hamiltonian. +""" function split_into_clusters(ig::LabelledGraph{G, L}, assignment_rule) where {G, L} cluster_id_to_verts = Dict(i => L[] for i in values(assignment_rule)) for v in vertices(ig) push!(cluster_id_to_verts[assignment_rule[v]], v) end @@ -21,8 +34,22 @@ function split_into_clusters(ig::LabelledGraph{G, L}, assignment_rule) where {G, end """ -Create factor graph. -Factor graph order introduced as a natural order in factor graph coordinates. +Create a clustered Hamiltonian. + +This function constructs a clustered Hamiltonian from an Ising graph by introducing a natural order in clustered Hamiltonian coordinates. + +# Arguments: +- `ig::IsingGraph`: The Ising graph representing the spin system. +- `num_states_cl::Int`: The number of states per cluster. +- `spectrum::Function`: A function for calculating the spectrum of the clustered Hamiltonian. +- `cluster_assignment_rule::Dict{Int, L}`: A dictionary specifying the assignment rule that maps Ising graph vertices to clusters. + +# Returns: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. + +The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by introducing a natural order in clustered Hamiltonian coordinates. It allows you to specify the number of states per cluster, a spectrum calculation function, and a cluster assignment rule, which maps Ising graph vertices to clusters. + +This function is useful for organizing and studying spin systems in a clustered Hamiltonian framework. """ function clustered_hamiltonian( ig::IsingGraph, @@ -34,7 +61,25 @@ function clustered_hamiltonian( clustered_hamiltonian(ig, ns, spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end +""" +Create a clustered Hamiltonian. + +This function constructs a clustered Hamiltonian from an Ising graph by introducing a natural order in clustered Hamiltonian coordinates. + +# Arguments: +- `ig::IsingGraph`: The Ising graph representing the spin system. +- `num_states_cl::Dict{T, Int}`: A dictionary specifying the number of states per cluster for different clusters. +- `spectrum::Function`: A function for calculating the spectrum of the clustered Hamiltonian. +- `cluster_assignment_rule::Dict{Int, T}`: A dictionary specifying the assignment rule that maps Ising graph vertices to clusters. +# Returns: +- `cl_h::LabelledGraph{MetaDiGraph}`: The clustered Hamiltonian represented as a labeled graph. + +The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by introducing a natural order in clustered Hamiltonian coordinates. It allows you to specify the number of states per cluster, a spectrum calculation function, and a cluster assignment rule, which maps Ising graph vertices to clusters. + +This function is useful for organizing and studying spin systems in a clustered Hamiltonian framework. + +""" function clustered_hamiltonian( ig::IsingGraph, num_states_cl::Dict{T, Int}; @@ -82,6 +127,25 @@ function clustered_hamiltonian( cl_h end +""" +Create a clustered Hamiltonian with optional cluster sizes. + +This function constructs a clustered Hamiltonian from an Ising graph by introducing a natural order in clustered Hamiltonian coordinates. + +# Arguments: +- `ig::IsingGraph`: The Ising graph representing the spin system. +- `spectrum::Function`: A function for calculating the spectrum of the clustered Hamiltonian. +- `cluster_assignment_rule::Dict{Int, T}`: A dictionary specifying the assignment rule that maps Ising graph vertices to clusters. + +# Returns: +- `cl_h::LabelledGraph{MetaDiGraph}`: The clustered Hamiltonian represented as a labeled graph. + +The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by introducing a natural order in clustered Hamiltonian coordinates. You can optionally specify a spectrum calculation function and a cluster assignment rule, which maps Ising graph vertices to clusters. + +If you want to specify custom cluster sizes, use the alternative version of this function by passing a `Dict{T, Int}` containing the number of states per cluster as `num_states_cl`. + +This function is useful for organizing and studying spin systems in a clustered Hamiltonian framework. +""" function clustered_hamiltonian( ig::IsingGraph; spectrum::Function=full_spectrum, @@ -90,7 +154,24 @@ function clustered_hamiltonian( clustered_hamiltonian(ig, Dict{T, Int}(), spectrum=spectrum, cluster_assignment_rule=cluster_assignment_rule) end -function rank_reveal(energy, order=:PE) where T <: Real #TODO: add type +""" +Reveal ranks and energies in a specified order. + +This function calculates and reveals the ranks and energies of a set of states in either the 'PE' (Projector Energy) or 'EP' (Energy Projector) order. + +# Arguments: +- `energy`: The energy values of states. +- `order::Symbol`: The order in which to reveal the ranks and energies. It can be either `:PE` for 'Projector Energy)' order (default) or `:EP` for 'Energy Projector' order. + +# Returns: +- If `order` is `:PE`, the function returns a tuple `(P, E)` where: + - `P`: A permutation matrix representing projectors. + - `E`: An array of energy values. +- If `order` is `:EP`, the function returns a tuple `(E, P)` where: + - `E`: An array of energy values. + - `P`: A permutation matrix representing projectors. +""" +function rank_reveal(energy, order=:PE) #TODO: add type @assert order ∈ (:PE, :EP) dim = order == :PE ? 1 : 2 E, idx = unique_dims(energy, dim) @@ -99,9 +180,20 @@ function rank_reveal(energy, order=:PE) where T <: Real #TODO: add type end """ -Returns Dict(vertex of ising graph -> spin value) -Assumes that state has the same order as vertices in factor graph! TODO: check the order consistency over external packages. + +Decode a clustered Hamiltonian state into Ising graph spin values. + +This function decodes a state from a clustered Hamiltonian into Ising graph spin values and returns a dictionary mapping each Ising graph vertex to its corresponding spin value. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `state::Vector{Int}`: The state to be decoded, represented as an array of state indices for each vertex in the clustered Hamiltonian. + +# Returns: +- `spin_values::Dict{Int, Int}`: A dictionary mapping each Ising graph vertex to its corresponding spin value. + +This function assumes that the state has the same order as the vertices in the factor graph (clustered Hamiltonian). It decodes the state consistently based on the cluster assignments and spectra of the clustered Hamiltonian. """ function decode_clustered_hamiltonian_state(cl_h::LabelledGraph{S, T}, state::Vector{Int}) where {S, T} ret = Dict{Int, Int}() @@ -116,7 +208,20 @@ function decode_clustered_hamiltonian_state(cl_h::LabelledGraph{S, T}, state::Ve ret end +""" +Calculate the energy of a clustered Hamiltonian state. + +This function calculates the energy of a given state in a clustered Hamiltonian. The state is represented as a dictionary mapping each Ising graph vertex to its corresponding spin value. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `σ::Dict{T, Int}`: A dictionary mapping Ising graph vertices to their spin values. +# Returns: +- `en_cl_h::Float64`: The energy of the state in the clustered Hamiltonian. + +This function computes the energy by summing the energies associated with individual clusters and the interaction energies between clusters. It takes into account the cluster spectra and projectors stored in the clustered Hamiltonian. +""" function energy(cl_h::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_cl_h = 0.0 for v ∈ vertices(cl_h) en_cl_h += get_prop(cl_h, v, :spectrum).energies[σ[v]] end @@ -131,7 +236,21 @@ function energy(cl_h::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_cl_h end +""" +Calculate the interaction energy between two nodes in a clustered Hamiltonian. + +This function computes the interaction energy between two specified nodes in a clustered Hamiltonian, represented as a labeled graph. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `i::Int`: The index of the first site. +- `j::Int`: The index of the second site. + +# Returns: +- `int_eng::AbstractMatrix{T}`: The interaction energy matrix between the specified sites. +The function checks if there is an interaction edge between the two sites (i, j) in both directions (i -> j and j -> i). If such edges exist, it retrieves the interaction energy matrix, projectors, and calculates the interaction energy. If no interaction edge is found, it returns a zero matrix. +""" function energy_2site(cl_h::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} # matrix of interaction energies between two nodes if has_edge(cl_h, (i, j, 1), (i, j, 2)) @@ -154,6 +273,22 @@ function energy_2site(cl_h::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} int_eng end +""" +Calculate the bond energy between two clusters in a clustered Hamiltonian. + +This function computes the bond energy between two specified clusters (cluster nodes) in a clustered Hamiltonian, represented as a labeled graph. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `cl_h_u::NTuple{N, Int64}`: The coordinates of the first cluster. +- `cl_h_v::NTuple{N, Int64}`: The coordinates of the second cluster. +- `σ::Int`: The Ising spin value for which the bond energy is calculated. + +# Returns: +- `energies::AbstractVector{T}`: The bond energy vector between the two clusters for the specified Ising spin value. + +The function checks if there is an edge between the two clusters (u -> v and v -> u). If such edges exist, it retrieves the bond energy matrix and projectors and calculates the bond energy. If no bond edge is found, it returns a zero vector. +""" function bond_energy( cl_h::LabelledGraph{S, T}, cl_h_u::NTuple{N, Int64}, @@ -179,10 +314,39 @@ function bond_energy( end end +""" +Get the size of a cluster in a clustered Hamiltonian. + +This function returns the size (number of states) of a cluster in a clustered Hamiltonian, represented as a labeled graph. + +# Arguments: +- `clustered_hamiltonian::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `vertex::T`: The vertex (cluster) for which the size is to be determined. + +# Returns: +- `size::Int`: The number of states in the specified cluster. + +The function retrieves the spectrum associated with the specified cluster and returns the length of the energy vector in that spectrum. +""" function cluster_size(clustered_hamiltonian::LabelledGraph{S, T}, vertex::T) where {S, T} length(get_prop(clustered_hamiltonian, vertex, :spectrum).energies) end +""" +Calculate the exact conditional probability of a target state in a clustered Hamiltonian. + +This function computes the exact conditional probability of a specified target state in a clustered Hamiltonian, represented as a labeled graph. + +# Arguments: +- `clustered_hamiltonian::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `beta`: The inverse temperature parameter. +- `target_state::Dict`: A dictionary specifying the target state as a mapping of cluster vertices to Ising spin values. + +# Returns: +- `prob::Float64`: The exact conditional probability of the target state. + +The function generates all possible states for the clusters in the clustered Hamiltonian, calculates their energies, and computes the probability distribution based on the given inverse temperature parameter. It then calculates the conditional probability of the specified target state by summing the probabilities of states that match the target state. +""" function exact_cond_prob(clustered_hamiltonian::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors ver = vertices(clustered_hamiltonian) @@ -192,8 +356,26 @@ function exact_cond_prob(clustered_hamiltonian::LabelledGraph{S, T}, beta, targe prob = exp.(-beta .* energies) prob ./= sum(prob) sum(prob[findall([all(s[k] == v for (k, v) ∈ target_state) for s ∈ states])]) - end +end + +""" +Truncate a clustered Hamiltonian based on specified states. +This function truncates a given clustered Hamiltonian by selecting a subset of states for each cluster based on the provided `states` dictionary. +The resulting truncated Hamiltonian contains only the selected states for each cluster. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `states::Dict`: A dictionary specifying the states to be retained for each cluster. + +# Returns: +- `new_cl_h::LabelledGraph{MetaDiGraph}`: The truncated clustered Hamiltonian with reduced states. + +The function creates a new clustered Hamiltonian `new_cl_h` with the same structure as the input `cl_h`. +It then updates the spectrum of each cluster in `new_cl_h` by selecting the specified states from the original spectrum. +Additionally, it updates the interactions and projectors between clusters based on the retained states. +The resulting `new_cl_h` represents a truncated version of the original Hamiltonian. +""" function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) where {S, T} new_cl_h = LabelledGraph{MetaDiGraph}(vertices(cl_h)) diff --git a/src/ising.jl b/src/ising.jl index 7ad2f0f..ca8fc6f 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -10,7 +10,8 @@ export biases, couplings, IsingGraph, - prune + prune, + inter_cluster_edges const Instance = Union{String, Dict} const IsingGraph{T} = LabelledGraph{MetaGraph{Int, T}} @@ -20,7 +21,21 @@ function unique_nodes(ising_tuples) end """ -Creates Ising graph, convention: H = scale * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) +Create an Ising graph from interaction data. + +This function creates an Ising graph from interaction data provided in the form of an `inst` argument. The Ising graph represents a system of spins, where each spin is associated with a vertex, and interactions between spins are represented as edges with corresponding weights. + +# Arguments: +- `::Type{T}`: The type of the edge weights, typically `Float64` or `Float32`. +- `inst::Instance`: Interaction data, which can be either a file path to a CSV file or a collection of triples `(i, j, J)` representing interactions between spins, where `i` and `j` are spin indices, and `J` is the interaction strength. +- `scale::Real`: A scaling factor applied to interaction strengths (default is 1). +- `rank_override::Dict`: A dictionary specifying the rank (number of states) for each vertex. If not provided, a default rank of 2 is used for all vertices. + +# Returns: +- `ig::IsingGraph{T}`: The Ising graph representing the spin system. + +The function reads interaction data and constructs an Ising graph `ig`. It assigns interaction strengths to edges between spins and optionally scales them by the `scale` factor. The `rank_override` dictionary can be used to specify the rank (number of states) for individual vertices, allowing customization of the Ising model. +Convention: H = scale * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) """ function ising_graph(::Type{T}, inst::Instance; scale::Real=1, rank_override::Dict=Dict{Int, Int}()) where T if inst isa String @@ -55,6 +70,19 @@ rank_vec(ig::IsingGraph) = Int[get_prop((ig), v, :rank) for v ∈ vertices(ig)] basis_size(ig::IsingGraph) = prod(rank_vec(ig)) biases(ig::IsingGraph) = get_prop.(Ref(ig), vertices(ig), :h) +""" +Return the coupling strengths between vertices of an Ising graph. + +This function computes and returns the coupling strengths (interaction energies) between pairs of vertices in an Ising graph `ig`. The coupling strengths are represented as a matrix, where each element `(i, j)` corresponds to the interaction energy between vertex `i` and vertex `j`. + +# Arguments: +- `ig::IsingGraph{T}`: The Ising graph representing a system of spins with associated interaction strengths. + +# Returns: +- `J::Matrix{T}`: A matrix of coupling strengths between vertices of the Ising graph. + +The function iterates over the edges of the Ising graph and extracts the interaction strengths associated with each edge, populating the `J` matrix accordingly. +""" function couplings(ig::IsingGraph{T}) where T J = zeros(T, nv(ig), nv(ig)) for edge ∈ edges(ig) @@ -67,7 +95,20 @@ end cluster(ig::IsingGraph, verts) = induced_subgraph(ig, collect(verts)) """ -Returns dense adjacency matrix between clusters. +Return the dense adjacency matrix between clusters of vertices in an Ising graph. + +This function computes and returns the dense adjacency matrix `J` between clusters of vertices represented by two Ising graphs, `cl1` and `cl2`, within the context of the larger Ising graph `ig`. The adjacency matrix represents the interaction strengths between clusters of vertices, where each element `(i, j)` corresponds to the interaction strength between cluster `i` in `cl1` and cluster `j` in `cl2`. + +# Arguments: +- `ig::IsingGraph{T}`: The Ising graph representing a system of spins with associated interaction strengths. +- `cl1::IsingGraph{T}`: The first Ising graph representing one cluster of vertices. +- `cl2::IsingGraph{T}`: The second Ising graph representing another cluster of vertices. + +# Returns: +- `outer_edges::Vector{LabelledEdge}`: A vector of labeled edges representing the interactions between clusters. +- `J::Matrix{T}`: A dense adjacency matrix representing interaction strengths between clusters. + +The function first identifies the outer edges that connect vertices between the two clusters in the context of the larger Ising graph `ig`. It then computes the interaction strengths associated with these outer edges and populates the dense adjacency matrix `J` accordingly. """ function inter_cluster_edges(ig::IsingGraph{T}, cl1::IsingGraph{T}, cl2::IsingGraph{T}) where T outer_edges = [LabelledEdge(i, j) for i ∈ vertices(cl1), j ∈ vertices(cl2) if has_edge(ig, i, j)] @@ -80,8 +121,19 @@ function inter_cluster_edges(ig::IsingGraph{T}, cl1::IsingGraph{T}, cl2::IsingGr end """ -Get rid of non-existing spins. Used only in MPS_search, would be obsolete if MPS_search uses QMps. +Remove non-existing spins from an Ising graph. + +This function removes non-existing spins from the given Ising graph `ig`. Non-existing spins are those that have zero degree (no connections to other spins) and also have an external magnetic field (`h`) that is not approximately equal to zero within the specified tolerance `atol`. + +# Arguments: +- `ig::IsingGraph`: The Ising graph to be pruned. +- `atol::Real`: The tolerance for considering the external magnetic field as zero. The default value is `1e-14`. + +# Returns: +- `pruned_graph::IsingGraph`: A new Ising graph with non-existing spins removed. + +The function returns a pruned version of the input Ising graph, where non-existing spins and their associated properties are removed. """ function prune(ig::IsingGraph; atol::Real=1e-14) to_keep = vcat( diff --git a/src/lattice.jl b/src/lattice.jl index ac71d5a..9ed4106 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -9,13 +9,39 @@ export zephyr_lattice_5tuple_rotated, periodic_lattice -"Variable number of Ising graph -> Factor graph coordinate system" +""" +Create a mapping from factor graph coordinates to a super square lattice arrangement. +Variable number of Ising graph -> Factor graph coordinate system + +This function generates a mapping that relates factor graph coordinates to a super square lattice arrangement. The super square lattice is defined by the size of five dimensions: `(m, um, n, un, t)`. + +# Arguments: +- `size::NTuple{5, Int}`: A tuple specifying the size of the super square lattice in five dimensions: `(m, um, n, un, t)`. + +# Returns: +- `coord_map::Dict`: A dictionary that maps factor graph coordinates to the corresponding lattice coordinates. + +The `size` tuple represents the dimensions of the super square lattice. The function creates a dictionary where factor graph coordinates are associated with their corresponding lattice coordinates. +""" function super_square_lattice(size::NTuple{5, Int}) m, um, n, un, t = size old = LinearIndices((1:t, 1:un, 1:n, 1:um, 1:m)) Dict(old[k, uj, j, ui, i] => (i, j) for i=1:m, ui=1:um, j=1:n, uj=1:un, k=1:t) end +""" +Create a mapping from factor graph coordinates to a simplified super square lattice arrangement. + +This function generates a mapping that relates factor graph coordinates to a simplified super square lattice arrangement. The simplified super square lattice is defined by the size of three dimensions: `(m, n, t)`. + +# Arguments: +- `size::NTuple{3, Int}`: A tuple specifying the size of the simplified super square lattice in three dimensions: `(m, n, t)`. + +# Returns: +- `coord_map::Dict`: A dictionary that maps factor graph coordinates to the corresponding lattice coordinates. + +The `size` tuple represents the dimensions of the simplified super square lattice. The function internally adds the required dimensions `(1, 1)` to make it compatible with the `super_square_lattice` function, which deals with five dimensions. +""" function super_square_lattice(size::NTuple{3, Int}) m, n, t = size super_square_lattice((m, 1, n, 1, t)) @@ -23,6 +49,19 @@ end pegasus_lattice(size::NTuple{2, Int}) = pegasus_lattice((size[1], size[2], 3)) +""" +Create a mapping from factor graph coordinates to Pegasus lattice coordinates. + +This function generates a mapping that relates factor graph coordinates to Pegasus lattice coordinates based on the specified size of the Pegasus lattice in three dimensions: `(m, n, t)`. + +# Arguments: +- `size::NTuple{3, Int}`: A tuple specifying the size of the Pegasus lattice in three dimensions: `(m, n, t)`. + +# Returns: +- `coord_map::Dict`: A dictionary that maps factor graph coordinates to the corresponding Pegasus lattice coordinates. + +The Pegasus lattice is a specialized lattice used in quantum computing, and this function allows you to convert between factor graph coordinates and Pegasus lattice coordinates. +""" function pegasus_lattice(size::NTuple{3, Int}) m, n, t = size old = LinearIndices((1:8*t, 1:n, 1:m)) @@ -82,6 +121,19 @@ end zephyr_lattice(size::NTuple{2, Int}) = zephyr_lattice((size[1], size[2], 4)) +""" +Create a mapping from factor graph coordinates to Zephyr lattice coordinates. + +This function generates a mapping that relates factor graph coordinates to Zephyr lattice coordinates based on the specified size of the Zephyr lattice in three dimensions: `(m, n, t)`. + +# Arguments: +- `size::NTuple{3, Int}`: A tuple specifying the size of the Zephyr lattice in three dimensions: `(m, n, t)`. + +# Returns: +- `coord_map::Dict`: A dictionary that maps factor graph coordinates to the corresponding Zephyr lattice coordinates. + +The Zephyr lattice is a specialized lattice used in quantum computing, and this function allows you to convert between factor graph coordinates and Zephyr lattice coordinates. +""" function zephyr_lattice(size::NTuple{3, Int}) m, n, t = size zephyr_lattice_5tuple_rotated(m+1, n+1, zephyr_lattice_5tuple((Int(m/2), Int(n/2), t))) diff --git a/src/projectors.jl b/src/projectors.jl index 56a6ef7..29e5d1c 100644 --- a/src/projectors.jl +++ b/src/projectors.jl @@ -1,10 +1,23 @@ export PoolOfProjectors, get_projector!, - add_projector! + add_projector!, + empty! const Proj{T} = Union{Vector{T}, CuArray{T, 1}} +""" +`PoolOfProjectors` is a data structure for managing projectors associated with Ising model sites. It allows efficient storage and retrieval of projectors based on their indices and provides support for different computational devices. + + # Fields: + - `data::Dict{Symbol, Dict{Int, Proj{T}}}`: A dictionary that stores projectors associated with different computational devices (`:CPU`, `:GPU`, etc.). The inner dictionary maps site indices to projectors. + - `default_device::Symbol`: A symbol representing the default computational device for projectors in the pool. + - `sizes::Dict{Int, Int}`: A dictionary that maps site indices to the maximum projector size for each site. + + # Constructors: + - `PoolOfProjectors(data::Dict{Int, Dict{Int, Vector{T}}}) where T`: Create a `PoolOfProjectors` with initial data for projectors. The data is provided as a dictionary that maps site indices to projectors stored in different computational devices. The `sizes` dictionary is automatically populated based on the maximum projector size for each site. + - `PoolOfProjectors{T}() where T`: Create an empty `PoolOfProjectors` with no projectors initially stored. +""" struct PoolOfProjectors{T <: Integer} data::Dict{Symbol, Dict{Int, Proj{T}}} default_device::Symbol @@ -25,6 +38,15 @@ Base.eltype(lp::PoolOfProjectors{T}) where T = T Base.length(lp::PoolOfProjectors) = length(lp.data[lp.default_device]) Base.length(lp::PoolOfProjectors, device::Symbol) = length(lp.data[device]) +""" +Empty the pool of projectors associated with a specific computational device. + +This function removes all projectors stored on the specified computational device, freeing up memory resources. + +# Arguments: +- `lp::PoolOfProjectors`: The `PoolOfProjectors` object containing projectors. +- `device::Symbol`: The computational device for which projectors should be emptied (e.g., `:CPU`, `:GPU`). +""" function Base.empty!(lp::PoolOfProjectors, device::Symbol) if device ∈ keys(lp.data) empty!(lp.data[device]) @@ -36,7 +58,21 @@ Base.size(lp::PoolOfProjectors, index::Int) = lp.sizes[index] get_projector!(lp::PoolOfProjectors, index::Int) = get_projector!(lp, index, lp.default_device) -# TODO This is version for only one GPU +""" +TODO This is version for only one GPU + +Retrieve or create a projector from the `PoolOfProjectors` associated with a specific device. + +This function retrieves a projector from the `PoolOfProjectors` if it already exists. If the projector does not exist in the pool, it creates a new one and stores it for future use on the specified computational device. + +# Arguments: +- `lp::PoolOfProjectors{T}`: The `PoolOfProjectors` object containing projectors. +- `index::Int`: The index of the projector to retrieve or create. +- `device::Symbol`: The computational device on which the projector should be stored or retrieved (e.g., `:CPU`, `:GPU`). + +# Returns: +- `Proj{T}`: The projector of type `T` associated with the specified index and device. +""" function get_projector!(lp::PoolOfProjectors{T}, index::Int, device::Symbol) where T <: Integer if device ∉ keys(lp.data) push!(lp.data, device => Dict{Int, Proj{T}}()) @@ -55,6 +91,18 @@ function get_projector!(lp::PoolOfProjectors{T}, index::Int, device::Symbol) whe lp.data[device][index] end +""" +Add a projector to the `PoolOfProjectors` and associate it with an index. + +This function adds a projector `p` to the `PoolOfProjectors`. The `PoolOfProjectors` stores projectors based on their computational device (e.g., CPU or GPU) and assigns a unique index to each projector. The index can be used to retrieve the projector later using `get_projector!`. + +# Arguments: +- `lp::PoolOfProjectors{T}`: The `PoolOfProjectors` object to which the projector should be added. +- `p::Proj`: The projector to be added to the pool. The type of the projector `Proj` should match the type `T` specified in the `PoolOfProjectors`. + +# Returns: +- `Int`: The unique index associated with the added projector in the pool. +""" function add_projector!(lp::PoolOfProjectors{T}, p::Proj) where T <: Integer if lp.default_device == :CPU p = Array{T}(p) diff --git a/src/spectrum.jl b/src/spectrum.jl index 35878fd..0a48858 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -16,6 +16,20 @@ all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank).. const State = Vector{Int} +""" +A `Spectrum` represents the energy spectrum of a system. + +A `Spectrum` consists of energy levels, their corresponding states, and integer representations of the states. + +# Fields: +- `energies::Vector{<:Real}`: An array of energy levels. +- `states::AbstractArray{State}`: An array of states. +- `states_int::Vector{Int}`: An array of integer representations of states. + +# Constructors: +- `Spectrum(energies, states, states_int)`: Creates a `Spectrum` object with the specified energy levels, states, and integer representations. +- `Spectrum(energies, states)`: Creates a `Spectrum` object with the specified energy levels and states, automatically generating integer representations. +""" struct Spectrum energies::Vector{<:Real} states::AbstractArray{State} @@ -29,17 +43,52 @@ struct Spectrum end end +""" +Converts a matrix of binary vectors to their integer representations. + +This function takes a matrix of binary vectors, where each row represents a binary vector, and converts them into their corresponding integer representations. + +# Arguments: +- `matrix::Vector{Vector{T}}`: A matrix of binary vectors. + +# Returns: +- `Vector{Int}`: An array of integer representations of the binary vectors. +""" function matrix_to_integers(matrix::Vector{Vector{T}}) where T nrows = length(matrix[1]) multipliers = 2 .^ collect(0:nrows-1) div.((hcat(matrix...)' .+ 1) , 2) * multipliers end +""" +Calculates the energy of a state in an Ising graph. + +This function calculates the energy of a given state in the context of an Ising graph. The energy is computed based on the interactions between spins and their associated biases. + +# Arguments: +- `σ::AbstractArray{State}`: An array representing the state of spins in the Ising graph. +- `ig::IsingGraph`: The Ising graph defining the interactions and biases. + +# Returns: +- `Vector{Float64}`: An array of energy values for each state. +""" function energy(σ::AbstractArray{State}, ig::IsingGraph) J, h = couplings(ig), biases(ig) dot.(σ, Ref(J), σ) + dot.(Ref(h), σ) end +""" +Calculates the energy of a state in an Ising graph. + +This function computes the energy of a given state in the context of an Ising graph. The energy is calculated based on the interactions between spins and their associated biases. + +# Arguments: +- `ig::IsingGraph{T}`: The Ising graph defining the interactions and biases. +- `ig_state::Dict{Int, Int}`: A dictionary mapping spin indices to their corresponding states. + +# Returns: +- `T`: The energy of the state in the Ising graph. +""" function energy(ig::IsingGraph{T}, ig_state::Dict{Int, Int}) where T en = zero(T) for (i, σ) ∈ ig_state @@ -55,6 +104,17 @@ function energy(ig::IsingGraph{T}, ig_state::Dict{Int, Int}) where T en end +""" +Generates the energy spectrum for an Ising graph. + +This function computes the energy spectrum (energies and corresponding states) for a given Ising graph. The energy spectrum represents all possible energy levels and their associated states in the Ising graph. + +# Arguments: +- `ig::IsingGraph{T}`: The Ising graph for which the energy spectrum is generated. + +# Returns: +- `Spectrum`: An instance of the `Spectrum` type containing the energy levels and states. +""" function Spectrum(ig::IsingGraph{T}) where T L = nv(ig) N = 2^L @@ -70,6 +130,18 @@ function Spectrum(ig::IsingGraph{T}) where T Spectrum(energies, states) end +""" +Computes the Gibbs tensor for an Ising graph at a given inverse temperature. + +This function calculates the Gibbs tensor for an Ising graph at a specified inverse temperature (β). The Gibbs tensor represents the conditional probabilities of states given the inverse temperature and the Ising graph. + +# Arguments: +- `ig::IsingGraph{T}`: The Ising graph for which the Gibbs tensor is computed. +- `β::T (optional)`: The inverse temperature parameter. Default is 1. + +# Returns: +- `Matrix{T}`: A matrix representing the Gibbs tensor with conditional probabilities. +""" function gibbs_tensor(ig::IsingGraph{T}, β::T=1) where T σ = collect.(all_states(rank_vec(ig))) ρ = exp.(-β .* energy(σ, ig)) @@ -80,7 +152,22 @@ function brute_force(ig::IsingGraph, s::Symbol=:CPU; num_states::Int=1) brute_force(ig, Val(s); num_states) end -#TODO only one of brute_force and full_spectrum should remain +""" +TODO only one of brute_force and full_spectrum should remain + +Performs brute-force calculation of the lowest-energy states and their energies for an Ising graph. + +This function exhaustively computes the lowest-energy states and their corresponding energies for an Ising graph. +The calculation is done using brute-force enumeration, making it feasible only for small Ising graphs. + +# Arguments: +- `ig::IsingGraph{T}`: The Ising graph for which the lowest-energy states are computed. +- `::Val{:CPU}`: A value indicating that the computation is performed on the CPU. +- `num_states::Int (optional)`: The maximum number of lowest-energy states to calculate. Default is 1. + +# Returns: +- `Spectrum`: A `Spectrum` object containing the lowest-energy states and their energies. +""" function brute_force(ig::IsingGraph{T}, ::Val{:CPU}; num_states::Int=1) where T L = nv(ig) L == 0 && return Spectrum(zeros(T, 1), Vector{Vector{Int}}[], zeros(T, 1)) diff --git a/src/truncate.jl b/src/truncate.jl index 4107720..2da4e79 100644 --- a/src/truncate.jl +++ b/src/truncate.jl @@ -1,9 +1,25 @@ export truncate_clustered_hamiltonian_2site_energy, truncate_clustered_hamiltonian_1site_BP, - truncate_clustered_hamiltonian_2site_BP + truncate_clustered_hamiltonian_2site_BP, + select_numstate_best +""" +Truncates a clustered Hamiltonian using belief propagation (BP) for a single site cluster. +This function employs belief propagation (BP) to approximate the most probable states and energies for a clustered Hamiltonian +associated with a single-site cluster. It then truncates the clustered Hamiltonian based on the most probable states. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `num_states::Int`: The maximum number of most probable states to keep. +- `beta::Real (optional)`: The inverse temperature parameter for the BP algorithm. Default is 1.0. +- `tol::Real (optional)`: The tolerance value for convergence in BP. Default is 1e-10. +- `iter::Int (optional)`: The maximum number of BP iterations. Default is 1. + +# Returns: +- `LabelledGraph{S, T}`: A truncated clustered Hamiltonian. +""" function truncate_clustered_hamiltonian_1site_BP( cl_h::LabelledGraph{S, T}, num_states::Int; @@ -20,6 +36,19 @@ function truncate_clustered_hamiltonian_1site_BP( truncate_clustered_hamiltonian(cl_h, states) end +""" +Truncate a clustered Hamiltonian based on 2-site energy states. + +This function truncates a clustered Hamiltonian by considering 2-site energy states and selecting the most probable states +to keep. It computes the energies for all 2-site combinations and selects the states that maximize the probability. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `num_states::Int`: The maximum number of most probable states to keep. + +# Returns: +- `LabelledGraph{S, T}`: A truncated clustered Hamiltonian. +""" function truncate_clustered_hamiltonian_2site_energy(cl_h::LabelledGraph{S, T}, num_states::Int) where {S, T} # TODO: name to be clean to make it consistent with square2 and squarestar2 states = Dict() @@ -38,6 +67,21 @@ function truncate_clustered_hamiltonian_2site_energy(cl_h::LabelledGraph{S, T}, truncate_clustered_hamiltonian(cl_h, states) end +""" +Truncate a clustered Hamiltonian based on 2-site belief propagation states. + +This function truncates a clustered Hamiltonian by considering 2-site belief propagation states and selecting the most probable states +to keep. It computes the beliefs for all 2-site combinations and selects the states that maximize the probability. + +# Arguments: +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `beliefs::Dict`: A dictionary containing belief values for 2-site interactions. +- `num_states::Int`: The maximum number of most probable states to keep. +- `beta::Real (optional)`: The inverse temperature parameter (default is 1.0). + +# Returns: +- `LabelledGraph{S, T}`: A truncated clustered Hamiltonian. +""" function truncate_clustered_hamiltonian_2site_BP( cl_h::LabelledGraph{S, T}, beliefs::Dict, @@ -58,11 +102,20 @@ function truncate_clustered_hamiltonian_2site_BP( truncate_clustered_hamiltonian(cl_h, states) end -function select_numstate_best(E, sx, num_states) - # truncate based on energy in two nodes of factor graph; - # resulting states are a product of states in two nodes, - # so we have to fine-tune to end up with expected number of states +""" +Select a specified number of best states based on energy. +This function selects a specified number of best states from a list of energies based on energy values in two nodes of clustered hamiltonian. It fine-tunes the selection to ensure that the resulting states have the expected number. + +# Arguments: +- `E::Vector{Real}`: A vector of energy values. +- `sx::Int`: The size of the factor graph for one of the nodes. +- `num_states::Int`: The desired number of states to select. + +# Returns: +- `Tuple{Vector{Int}, Vector{Int}}`: A tuple containing two vectors of indices, `ind1` and `ind2`, which represent the selected states for two nodes of a factor graph. +""" +function select_numstate_best(E, sx, num_states) low, high = 1, min(num_states, length(E)) while true From 425a4be7bd3d305cad08c4cd5c9ea0b5c3cd6d6b Mon Sep 17 00:00:00 2001 From: annamariadziubyna <73058800+annamariadziubyna@users.noreply.github.com> Date: Tue, 3 Oct 2023 13:37:54 +0200 Subject: [PATCH 179/218] add $(TYPEDSIGNATURES) --- docs/src/userguide.md | 6 +++--- src/bp.jl | 20 ++++++++++++++++++ src/clustered_hamiltonian.jl | 40 ++++++++++++++++++++++++++++-------- src/ising.jl | 8 ++++++++ src/lattice.jl | 38 ++++++++++++++++++++-------------- src/projectors.jl | 8 ++++++++ src/spectrum.jl | 14 +++++++++++++ src/truncate.jl | 12 +++++++++-- src/utils.jl | 2 ++ test/utils.jl | 2 +- 10 files changed, 121 insertions(+), 29 deletions(-) diff --git a/docs/src/userguide.md b/docs/src/userguide.md index f31cca2..acdd7f6 100644 --- a/docs/src/userguide.md +++ b/docs/src/userguide.md @@ -65,7 +65,7 @@ instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, (1, 2) => -1.0, (2, 3) => 1.0) ig = ising_graph(instance) -# Create factor graph. +# Create clustered Hamiltonian. cl_h = clustered_hamiltonian( ig, cluster_assignment_rule = super_square_lattice((3, 1, 1)) @@ -95,7 +95,7 @@ cl_h = clustered_hamiltonian( cluster_assignment_rule = pegasus_lattice((m, n, t)) ) -println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in factor graph: ", length(LabelledGraphs.vertices(cl_h))) +println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))) ``` @@ -121,5 +121,5 @@ cl_h = clustered_hamiltonian( cluster_assignment_rule = zephyr_lattice((m, n, t)) ) -println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in factor graph: ", length(LabelledGraphs.vertices(cl_h))) +println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))) ``` \ No newline at end of file diff --git a/src/bp.jl b/src/bp.jl index f9ddb34..b9af2c7 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -12,6 +12,7 @@ export SparseCSC """ +$(TYPEDSIGNATURES) Perform belief propagation on a given clustered hamiltonian. # Arguments: @@ -89,6 +90,7 @@ function belief_propagation(cl_h::LabelledGraph{S, T}, beta::Real; tol=1e-6, ite end """ +$(TYPEDSIGNATURES) Returns the neighbors of a given vertex in a clustered Hamiltonian. # Arguments: @@ -123,6 +125,8 @@ function get_neighbors(cl_h::LabelledGraph{S, T}, vertex::NTuple) where {S, T} end """ +$(TYPEDSIGNATURES) + A custom Julia struct representing energy values in a merged format for use in specific calculations. # Fields: @@ -145,6 +149,8 @@ end Base.adjoint(s::MergedEnergy) = MergedEnergy(s.e11', s.e21', s.e12', s.e22') """ +$(TYPEDSIGNATURES) + Update a message using energy values and temperature. # Arguments: @@ -165,6 +171,8 @@ function update_message(E_bond::AbstractArray, message::Vector, beta::Real) end """ +$(TYPEDSIGNATURES) + Update a message using energy values and temperature in a merged energy format. # Arguments: @@ -225,6 +233,8 @@ function update_message(E_bond::MergedEnergy, message::Vector, beta::Real) end """ +$(TYPEDSIGNATURES) + Constructs a clustered Hamiltonian for a given clustered Hamiltonian with a 2-site cluster approximation. # Arguments: @@ -278,6 +288,8 @@ function clustered_hamiltonian_2site(cl_h::LabelledGraph{S, T}, beta::Real) wher end """ +$(TYPEDSIGNATURES) + Merge two vertices in a clustered Hamiltonian to create a single merged vertex. # Arguments: @@ -333,6 +345,8 @@ function merge_vertices_cl_h(cl_h::LabelledGraph{S, T}, β::Real, node1::NTuple{ end """ +$(TYPEDSIGNATURES) + Get the local energy associated with a vertex in a clustered Hamiltonian. # Arguments: @@ -351,6 +365,8 @@ function local_energy(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}) where {S, end """ +$(TYPEDSIGNATURES) + Get the interaction energy between two vertices in a clustered Hamiltonian. # Arguments: @@ -375,6 +391,8 @@ function interaction_energy(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::N end """ +$(TYPEDSIGNATURES) + Get the projector associated with an edge between two vertices in a clustered Hamiltonian. # Arguments: @@ -410,6 +428,8 @@ function outer_projector(p1::Array{T, 1}, p2::Array{T, 1}) where T <: Number end """ +$(TYPEDSIGNATURES) + Create a sparse column-compressed (CSC) matrix with specified column indices and values. # Arguments: diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index ad0b220..c8fd5bd 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -12,17 +12,19 @@ export cluster_size """ -Group spins into clusters based on an assignment rule, mapping factor graph coordinates to groups of spins in the Ising graph. -Dict(factor graph coordinates -> group of spins in Ising graph) +$(TYPEDSIGNATURES) + +Group spins into clusters based on an assignment rule, mapping clustered Hamiltonian coordinates to groups of spins in the Ising graph. +Dict(clustered Hamiltonian coordinates -> group of spins in Ising graph) # Arguments: - `ig::LabelledGraph{G, L}`: The Ising graph represented as a labeled graph. -- `assignment_rule`: A mapping that assigns Ising graph vertices to clusters based on factor graph coordinates. +- `assignment_rule`: A mapping that assigns Ising graph vertices to clusters based on clustered Hamiltonian coordinates. # Returns: - `clusters::Dict{L, Vertex}`: A dictionary mapping cluster identifiers to representative vertices in the Ising graph. -This function groups spins in the Ising graph into clusters based on an assignment rule. The assignment rule defines how factor graph coordinates correspond to clusters of spins in the Ising graph. Each cluster is represented by a vertex from the Ising graph. +This function groups spins in the Ising graph into clusters based on an assignment rule. The assignment rule defines how clustered Hamiltonian coordinates correspond to clusters of spins in the Ising graph. Each cluster is represented by a vertex from the Ising graph. The `split_into_clusters` function is useful for organizing and analyzing spins in complex spin systems, particularly in the context of clustered Hamiltonian. @@ -34,6 +36,8 @@ function split_into_clusters(ig::LabelledGraph{G, L}, assignment_rule) where {G, end """ +$(TYPEDSIGNATURES) + Create a clustered Hamiltonian. This function constructs a clustered Hamiltonian from an Ising graph by introducing a natural order in clustered Hamiltonian coordinates. @@ -62,6 +66,8 @@ function clustered_hamiltonian( end """ +$(TYPEDSIGNATURES) + Create a clustered Hamiltonian. This function constructs a clustered Hamiltonian from an Ising graph by introducing a natural order in clustered Hamiltonian coordinates. @@ -128,6 +134,8 @@ function clustered_hamiltonian( end """ +$(TYPEDSIGNATURES) + Create a clustered Hamiltonian with optional cluster sizes. This function constructs a clustered Hamiltonian from an Ising graph by introducing a natural order in clustered Hamiltonian coordinates. @@ -155,6 +163,8 @@ function clustered_hamiltonian( end """ +$(TYPEDSIGNATURES) + Reveal ranks and energies in a specified order. This function calculates and reveals the ranks and energies of a set of states in either the 'PE' (Projector Energy) or 'EP' (Energy Projector) order. @@ -180,6 +190,8 @@ function rank_reveal(energy, order=:PE) #TODO: add type end """ +$(TYPEDSIGNATURES) + TODO: check the order consistency over external packages. Decode a clustered Hamiltonian state into Ising graph spin values. @@ -193,7 +205,7 @@ This function decodes a state from a clustered Hamiltonian into Ising graph spin # Returns: - `spin_values::Dict{Int, Int}`: A dictionary mapping each Ising graph vertex to its corresponding spin value. -This function assumes that the state has the same order as the vertices in the factor graph (clustered Hamiltonian). It decodes the state consistently based on the cluster assignments and spectra of the clustered Hamiltonian. +This function assumes that the state has the same order as the vertices in the clustered Hamiltonian. It decodes the state consistently based on the cluster assignments and spectra of the clustered Hamiltonian. """ function decode_clustered_hamiltonian_state(cl_h::LabelledGraph{S, T}, state::Vector{Int}) where {S, T} ret = Dict{Int, Int}() @@ -209,6 +221,8 @@ function decode_clustered_hamiltonian_state(cl_h::LabelledGraph{S, T}, state::Ve end """ +$(TYPEDSIGNATURES) + Calculate the energy of a clustered Hamiltonian state. This function calculates the energy of a given state in a clustered Hamiltonian. The state is represented as a dictionary mapping each Ising graph vertex to its corresponding spin value. @@ -237,6 +251,8 @@ function energy(cl_h::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} end """ +$(TYPEDSIGNATURES) + Calculate the interaction energy between two nodes in a clustered Hamiltonian. This function computes the interaction energy between two specified nodes in a clustered Hamiltonian, represented as a labeled graph. @@ -274,6 +290,8 @@ function energy_2site(cl_h::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} end """ +$(TYPEDSIGNATURES) + Calculate the bond energy between two clusters in a clustered Hamiltonian. This function computes the bond energy between two specified clusters (cluster nodes) in a clustered Hamiltonian, represented as a labeled graph. @@ -282,10 +300,10 @@ This function computes the bond energy between two specified clusters (cluster n - `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. - `cl_h_u::NTuple{N, Int64}`: The coordinates of the first cluster. - `cl_h_v::NTuple{N, Int64}`: The coordinates of the second cluster. -- `σ::Int`: The Ising spin value for which the bond energy is calculated. +- `σ::Int`: Index for which the bond energy is calculated. # Returns: -- `energies::AbstractVector{T}`: The bond energy vector between the two clusters for the specified Ising spin value. +- `energies::AbstractVector{T}`: The bond energy vector between the two clusters for the specified index. The function checks if there is an edge between the two clusters (u -> v and v -> u). If such edges exist, it retrieves the bond energy matrix and projectors and calculates the bond energy. If no bond edge is found, it returns a zero vector. """ @@ -315,6 +333,8 @@ function bond_energy( end """ +$(TYPEDSIGNATURES) + Get the size of a cluster in a clustered Hamiltonian. This function returns the size (number of states) of a cluster in a clustered Hamiltonian, represented as a labeled graph. @@ -333,9 +353,11 @@ function cluster_size(clustered_hamiltonian::LabelledGraph{S, T}, vertex::T) whe end """ +$(TYPEDSIGNATURES) + Calculate the exact conditional probability of a target state in a clustered Hamiltonian. -This function computes the exact conditional probability of a specified target state in a clustered Hamiltonian, represented as a labeled graph. +This function computes the exact conditional probability of a specified target state in a clustered Hamiltonian, represented as a labelled graph. # Arguments: - `clustered_hamiltonian::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. @@ -359,6 +381,8 @@ function exact_cond_prob(clustered_hamiltonian::LabelledGraph{S, T}, beta, targe end """ +$(TYPEDSIGNATURES) + Truncate a clustered Hamiltonian based on specified states. This function truncates a given clustered Hamiltonian by selecting a subset of states for each cluster based on the provided `states` dictionary. diff --git a/src/ising.jl b/src/ising.jl index ca8fc6f..2b2639e 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -21,6 +21,8 @@ function unique_nodes(ising_tuples) end """ +$(TYPEDSIGNATURES) + Create an Ising graph from interaction data. This function creates an Ising graph from interaction data provided in the form of an `inst` argument. The Ising graph represents a system of spins, where each spin is associated with a vertex, and interactions between spins are represented as edges with corresponding weights. @@ -71,6 +73,8 @@ basis_size(ig::IsingGraph) = prod(rank_vec(ig)) biases(ig::IsingGraph) = get_prop.(Ref(ig), vertices(ig), :h) """ +$(TYPEDSIGNATURES) + Return the coupling strengths between vertices of an Ising graph. This function computes and returns the coupling strengths (interaction energies) between pairs of vertices in an Ising graph `ig`. The coupling strengths are represented as a matrix, where each element `(i, j)` corresponds to the interaction energy between vertex `i` and vertex `j`. @@ -95,6 +99,8 @@ end cluster(ig::IsingGraph, verts) = induced_subgraph(ig, collect(verts)) """ +$(TYPEDSIGNATURES) + Return the dense adjacency matrix between clusters of vertices in an Ising graph. This function computes and returns the dense adjacency matrix `J` between clusters of vertices represented by two Ising graphs, `cl1` and `cl2`, within the context of the larger Ising graph `ig`. The adjacency matrix represents the interaction strengths between clusters of vertices, where each element `(i, j)` corresponds to the interaction strength between cluster `i` in `cl1` and cluster `j` in `cl2`. @@ -121,6 +127,8 @@ function inter_cluster_edges(ig::IsingGraph{T}, cl1::IsingGraph{T}, cl2::IsingGr end """ +$(TYPEDSIGNATURES) + Used only in MPS_search, would be obsolete if MPS_search uses QMps. Remove non-existing spins from an Ising graph. diff --git a/src/lattice.jl b/src/lattice.jl index 9ed4106..e36df5a 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -10,18 +10,20 @@ export periodic_lattice """ -Create a mapping from factor graph coordinates to a super square lattice arrangement. +$(TYPEDSIGNATURES) + +Create a mapping from clustered Hamiltonian coordinates to a super square lattice arrangement. Variable number of Ising graph -> Factor graph coordinate system -This function generates a mapping that relates factor graph coordinates to a super square lattice arrangement. The super square lattice is defined by the size of five dimensions: `(m, um, n, un, t)`. +This function generates a mapping that relates clustered Hamiltonian coordinates to a super square lattice arrangement. The super square lattice is defined by the size of five dimensions: `(m, um, n, un, t)`. # Arguments: - `size::NTuple{5, Int}`: A tuple specifying the size of the super square lattice in five dimensions: `(m, um, n, un, t)`. # Returns: -- `coord_map::Dict`: A dictionary that maps factor graph coordinates to the corresponding lattice coordinates. +- `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding lattice coordinates. -The `size` tuple represents the dimensions of the super square lattice. The function creates a dictionary where factor graph coordinates are associated with their corresponding lattice coordinates. +The `size` tuple represents the dimensions of the super square lattice. The function creates a dictionary where clustered Hamiltonian coordinates are associated with their corresponding lattice coordinates. """ function super_square_lattice(size::NTuple{5, Int}) m, um, n, un, t = size @@ -30,15 +32,17 @@ function super_square_lattice(size::NTuple{5, Int}) end """ -Create a mapping from factor graph coordinates to a simplified super square lattice arrangement. +$(TYPEDSIGNATURES) + +Create a mapping from clustered Hamiltonian coordinates to a simplified super square lattice arrangement. -This function generates a mapping that relates factor graph coordinates to a simplified super square lattice arrangement. The simplified super square lattice is defined by the size of three dimensions: `(m, n, t)`. +This function generates a mapping that relates clustered Hamiltonian coordinates to a simplified super square lattice arrangement. The simplified super square lattice is defined by the size of three dimensions: `(m, n, t)`. # Arguments: - `size::NTuple{3, Int}`: A tuple specifying the size of the simplified super square lattice in three dimensions: `(m, n, t)`. # Returns: -- `coord_map::Dict`: A dictionary that maps factor graph coordinates to the corresponding lattice coordinates. +- `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding lattice coordinates. The `size` tuple represents the dimensions of the simplified super square lattice. The function internally adds the required dimensions `(1, 1)` to make it compatible with the `super_square_lattice` function, which deals with five dimensions. """ @@ -50,17 +54,19 @@ end pegasus_lattice(size::NTuple{2, Int}) = pegasus_lattice((size[1], size[2], 3)) """ -Create a mapping from factor graph coordinates to Pegasus lattice coordinates. +$(TYPEDSIGNATURES) -This function generates a mapping that relates factor graph coordinates to Pegasus lattice coordinates based on the specified size of the Pegasus lattice in three dimensions: `(m, n, t)`. +Create a mapping from clustered Hamiltonian coordinates to Pegasus lattice coordinates. + +This function generates a mapping that relates clustered Hamiltonian coordinates to Pegasus lattice coordinates based on the specified size of the Pegasus lattice in three dimensions: `(m, n, t)`. # Arguments: - `size::NTuple{3, Int}`: A tuple specifying the size of the Pegasus lattice in three dimensions: `(m, n, t)`. # Returns: -- `coord_map::Dict`: A dictionary that maps factor graph coordinates to the corresponding Pegasus lattice coordinates. +- `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding Pegasus lattice coordinates. -The Pegasus lattice is a specialized lattice used in quantum computing, and this function allows you to convert between factor graph coordinates and Pegasus lattice coordinates. +The Pegasus lattice is a specialized lattice used in quantum computing, and this function allows you to convert between clustered Hamiltonian coordinates and Pegasus lattice coordinates. """ function pegasus_lattice(size::NTuple{3, Int}) m, n, t = size @@ -122,17 +128,19 @@ end zephyr_lattice(size::NTuple{2, Int}) = zephyr_lattice((size[1], size[2], 4)) """ -Create a mapping from factor graph coordinates to Zephyr lattice coordinates. +$(TYPEDSIGNATURES) + +Create a mapping from clustered Hamiltonian coordinates to Zephyr lattice coordinates. -This function generates a mapping that relates factor graph coordinates to Zephyr lattice coordinates based on the specified size of the Zephyr lattice in three dimensions: `(m, n, t)`. +This function generates a mapping that relates clustered Hamiltonian coordinates to Zephyr lattice coordinates based on the specified size of the Zephyr lattice in three dimensions: `(m, n, t)`. # Arguments: - `size::NTuple{3, Int}`: A tuple specifying the size of the Zephyr lattice in three dimensions: `(m, n, t)`. # Returns: -- `coord_map::Dict`: A dictionary that maps factor graph coordinates to the corresponding Zephyr lattice coordinates. +- `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding Zephyr lattice coordinates. -The Zephyr lattice is a specialized lattice used in quantum computing, and this function allows you to convert between factor graph coordinates and Zephyr lattice coordinates. +The Zephyr lattice is a specialized lattice used in quantum computing, and this function allows you to convert between clustered Hamiltonian coordinates and Zephyr lattice coordinates. """ function zephyr_lattice(size::NTuple{3, Int}) m, n, t = size diff --git a/src/projectors.jl b/src/projectors.jl index 29e5d1c..ec16fcd 100644 --- a/src/projectors.jl +++ b/src/projectors.jl @@ -7,6 +7,8 @@ export const Proj{T} = Union{Vector{T}, CuArray{T, 1}} """ +$(TYPEDSIGNATURES) + `PoolOfProjectors` is a data structure for managing projectors associated with Ising model sites. It allows efficient storage and retrieval of projectors based on their indices and provides support for different computational devices. # Fields: @@ -39,6 +41,8 @@ Base.length(lp::PoolOfProjectors) = length(lp.data[lp.default_device]) Base.length(lp::PoolOfProjectors, device::Symbol) = length(lp.data[device]) """ +$(TYPEDSIGNATURES) + Empty the pool of projectors associated with a specific computational device. This function removes all projectors stored on the specified computational device, freeing up memory resources. @@ -59,6 +63,8 @@ Base.size(lp::PoolOfProjectors, index::Int) = lp.sizes[index] get_projector!(lp::PoolOfProjectors, index::Int) = get_projector!(lp, index, lp.default_device) """ +$(TYPEDSIGNATURES) + TODO This is version for only one GPU Retrieve or create a projector from the `PoolOfProjectors` associated with a specific device. @@ -92,6 +98,8 @@ function get_projector!(lp::PoolOfProjectors{T}, index::Int, device::Symbol) whe end """ +$(TYPEDSIGNATURES) + Add a projector to the `PoolOfProjectors` and associate it with an index. This function adds a projector `p` to the `PoolOfProjectors`. The `PoolOfProjectors` stores projectors based on their computational device (e.g., CPU or GPU) and assigns a unique index to each projector. The index can be used to retrieve the projector later using `get_projector!`. diff --git a/src/spectrum.jl b/src/spectrum.jl index 0a48858..78c465d 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -17,6 +17,8 @@ all_states(rank::Union{Vector, NTuple}) = Iterators.product(local_basis.(rank).. const State = Vector{Int} """ +$(TYPEDSIGNATURES) + A `Spectrum` represents the energy spectrum of a system. A `Spectrum` consists of energy levels, their corresponding states, and integer representations of the states. @@ -44,6 +46,8 @@ struct Spectrum end """ +$(TYPEDSIGNATURES) + Converts a matrix of binary vectors to their integer representations. This function takes a matrix of binary vectors, where each row represents a binary vector, and converts them into their corresponding integer representations. @@ -61,6 +65,8 @@ function matrix_to_integers(matrix::Vector{Vector{T}}) where T end """ +$(TYPEDSIGNATURES) + Calculates the energy of a state in an Ising graph. This function calculates the energy of a given state in the context of an Ising graph. The energy is computed based on the interactions between spins and their associated biases. @@ -78,6 +84,8 @@ function energy(σ::AbstractArray{State}, ig::IsingGraph) end """ +$(TYPEDSIGNATURES) + Calculates the energy of a state in an Ising graph. This function computes the energy of a given state in the context of an Ising graph. The energy is calculated based on the interactions between spins and their associated biases. @@ -105,6 +113,8 @@ function energy(ig::IsingGraph{T}, ig_state::Dict{Int, Int}) where T end """ +$(TYPEDSIGNATURES) + Generates the energy spectrum for an Ising graph. This function computes the energy spectrum (energies and corresponding states) for a given Ising graph. The energy spectrum represents all possible energy levels and their associated states in the Ising graph. @@ -131,6 +141,8 @@ function Spectrum(ig::IsingGraph{T}) where T end """ +$(TYPEDSIGNATURES) + Computes the Gibbs tensor for an Ising graph at a given inverse temperature. This function calculates the Gibbs tensor for an Ising graph at a specified inverse temperature (β). The Gibbs tensor represents the conditional probabilities of states given the inverse temperature and the Ising graph. @@ -153,6 +165,8 @@ function brute_force(ig::IsingGraph, s::Symbol=:CPU; num_states::Int=1) end """ +$(TYPEDSIGNATURES) + TODO only one of brute_force and full_spectrum should remain Performs brute-force calculation of the lowest-energy states and their energies for an Ising graph. diff --git a/src/truncate.jl b/src/truncate.jl index 2da4e79..db298d8 100644 --- a/src/truncate.jl +++ b/src/truncate.jl @@ -5,6 +5,8 @@ export select_numstate_best """ +$(TYPEDSIGNATURES) + Truncates a clustered Hamiltonian using belief propagation (BP) for a single site cluster. This function employs belief propagation (BP) to approximate the most probable states and energies for a clustered Hamiltonian @@ -37,6 +39,8 @@ function truncate_clustered_hamiltonian_1site_BP( end """ +$(TYPEDSIGNATURES) + Truncate a clustered Hamiltonian based on 2-site energy states. This function truncates a clustered Hamiltonian by considering 2-site energy states and selecting the most probable states @@ -68,6 +72,8 @@ function truncate_clustered_hamiltonian_2site_energy(cl_h::LabelledGraph{S, T}, end """ +$(TYPEDSIGNATURES) + Truncate a clustered Hamiltonian based on 2-site belief propagation states. This function truncates a clustered Hamiltonian by considering 2-site belief propagation states and selecting the most probable states @@ -103,17 +109,19 @@ function truncate_clustered_hamiltonian_2site_BP( end """ +$(TYPEDSIGNATURES) + Select a specified number of best states based on energy. This function selects a specified number of best states from a list of energies based on energy values in two nodes of clustered hamiltonian. It fine-tunes the selection to ensure that the resulting states have the expected number. # Arguments: - `E::Vector{Real}`: A vector of energy values. -- `sx::Int`: The size of the factor graph for one of the nodes. +- `sx::Int`: The size of the clustered Hamiltonian for one of the nodes. - `num_states::Int`: The desired number of states to select. # Returns: -- `Tuple{Vector{Int}, Vector{Int}}`: A tuple containing two vectors of indices, `ind1` and `ind2`, which represent the selected states for two nodes of a factor graph. +- `Tuple{Vector{Int}, Vector{Int}}`: A tuple containing two vectors of indices, `ind1` and `ind2`, which represent the selected states for two nodes of a clustered Hamiltonian. """ function select_numstate_best(E, sx, num_states) low, high = 1, min(num_states, length(E)) diff --git a/src/utils.jl b/src/utils.jl index 0f6cf27..16166a2 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -5,6 +5,8 @@ export import Base.Prehashed """ +$(TYPEDSIGNATURES) + Rewriten from Dwave-networkx m - Grid parameter for the Zephyr lattice. t - Tile parameter for the Zephyr lattice; must be even. diff --git a/test/utils.jl b/test/utils.jl index a5e9924..b5b86b3 100644 --- a/test/utils.jl +++ b/test/utils.jl @@ -1,7 +1,7 @@ instance_dir = "$(@__DIR__)/instances/pegasus/" instances = ["P2"] #, "P4", "P8", "P16"] -@testset verbose = true "Renumerated instances generate correct factor graph" begin +@testset verbose = true "Renumerated instances generate correct clustered Hamiltonian" begin size = [2, 4, 8, 16] @testset "$instance" for (i, instance) ∈ enumerate(instances) From 6e69a70e23df9366ea10f6c75fcd33b54ee6f6a3 Mon Sep 17 00:00:00 2001 From: annamariadziubyna <73058800+annamariadziubyna@users.noreply.github.com> Date: Thu, 5 Oct 2023 21:05:30 +0200 Subject: [PATCH 180/218] split the lines --- src/bp.jl | 69 +++++++++++++++++++++++++----------- src/clustered_hamiltonian.jl | 51 ++++++++++++++++++-------- src/ising.jl | 25 +++++++++---- src/lattice.jl | 24 ++++++++----- src/projectors.jl | 29 +++++++++------ src/spectrum.jl | 12 ++++--- src/truncate.jl | 6 ++-- 7 files changed, 149 insertions(+), 67 deletions(-) diff --git a/src/bp.jl b/src/bp.jl index b9af2c7..bc8286f 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -18,11 +18,13 @@ Perform belief propagation on a given clustered hamiltonian. # Arguments: - `cl_h::LabelledGraph{S, T}`: The clustered hamiltonian represented as a labeled graph. - `beta::Real`: The temperature parameter for the belief propagation algorithm. -- `tol::Real (optional, default=1e-6)`: The convergence tolerance. The algorithm stops when the message updates between iterations are smaller than this value. +- `tol::Real (optional, default=1e-6)`: The convergence tolerance. +The algorithm stops when the message updates between iterations are smaller than this value. - `iter::Int (optional, default=1)`: The maximum number of iterations to perform. # Returns: -- `beliefs::Dict`: A dictionary where keys are vertices of clustered hamiltonian, and values are the resulting beliefs after belief propagation. +- `beliefs::Dict`: A dictionary where keys are vertices of clustered hamiltonian, and values are the +resulting beliefs after belief propagation. The function implements belief propagation on the given clustered hamiltonian `cl_h` to calculate beliefs for each vertex. Belief propagation is an iterative algorithm that computes beliefs by passing messages between vertices and edges of the clustered hamiltonian. @@ -98,12 +100,15 @@ Returns the neighbors of a given vertex in a clustered Hamiltonian. - `vertex::NTuple`: The vertex for which neighbors are to be retrieved. # Returns: -- `neighbors::Vector{Tuple}`: A vector of tuples representing the neighbors of the specified vertex. Each tuple contains the following information: - - `dst_node::T`: The neighboring vertex. - - `pv::Matrix`: The projector associated with the edge connecting the vertex and its neighbor. - - `en::Real`: The energy associated with the edge connecting the vertex and its neighbor. - -This function retrieves the neighbors of a given vertex in a clustered Hamiltonian graph. It iterates through the edges of the graph and identifies edges connected to the specified vertex. For each neighboring edge, it extracts and returns the neighboring vertex, the associated projector, and the energy. +- `neighbors::Vector{Tuple}`: A vector of tuples representing the neighbors of the specified vertex. +Each tuple contains the following information: +- `dst_node::T`: The neighboring vertex. +- `pv::Matrix`: The projector associated with the edge connecting the vertex and its neighbor. +- `en::Real`: The energy associated with the edge connecting the vertex and its neighbor. + +This function retrieves the neighbors of a given vertex in a clustered Hamiltonian graph. +It iterates through the edges of the graph and identifies edges connected to the specified vertex. +For each neighboring edge, it extracts and returns the neighboring vertex, the associated projector, and the energy. """ function get_neighbors(cl_h::LabelledGraph{S, T}, vertex::NTuple) where {S, T} neighbors = [] @@ -135,9 +140,12 @@ A custom Julia struct representing energy values in a merged format for use in s - `e21::AbstractMatrix{T}` - `e22::AbstractMatrix{T}` -The `MergedEnergy` struct is used to represent energy values that are organized in a merged format. This format is often utilized in certain computational tasks, where energy values are categorized based on combinations of left and right factors. +The `MergedEnergy` struct is used to represent energy values that are organized in a merged format. +This format is often utilized in certain computational tasks, where energy values are categorized based on combinations of left and right factors. -Each field of the `MergedEnergy` struct stores energy values as an `AbstractMatrix{T}` of type `T`, where `T` is a subtype of the `Real` abstract type. The specific organization and interpretation of these energy values depend on the context in which this struct is used. +Each field of the `MergedEnergy` struct stores energy values as an `AbstractMatrix{T}` of type `T`, +where `T` is a subtype of the `Real` abstract type. +The specific organization and interpretation of these energy values depend on the context in which this struct is used. """ struct MergedEnergy{T <: Real} e11::AbstractMatrix{T} @@ -161,7 +169,9 @@ Update a message using energy values and temperature. # Returns: - `updated_message::Vector`: The updated message vector after applying the energy-based update. -This function takes energy values `E_bond` associated with a bond or interaction, an input message vector `message`, and a temperature parameter `beta`. It updates the message by first adjusting the energy values relative to their minimum value, exponentiating them with a negative sign and scaling by `beta`, and then multiplying them element-wise with the input message. +This function takes energy values `E_bond` associated with a bond or interaction, an input message vector `message`, +and a temperature parameter `beta`. It updates the message by first adjusting the energy values relative to their minimum value, +exponentiating them with a negative sign and scaling by `beta`, and then multiplying them element-wise with the input message. The result is an updated message that reflects the influence of energy values and temperature. """ @@ -183,9 +193,11 @@ Update a message using energy values and temperature in a merged energy format. # Returns: - `updated_message::Vector`: The updated message vector after applying the energy-based update. -This function takes energy values `E_bond` in a merged energy format, an input message vector `message`, and a temperature parameter `beta`. It updates the message based on the energy values and temperature using a specified algorithm. +This function takes energy values `E_bond` in a merged energy format, an input message vector `message`, +and a temperature parameter `beta`. It updates the message based on the energy values and temperature using a specified algorithm. -The `MergedEnergy` type represents energy values in a merged format, and the function processes these values accordingly to update the message vector. +The `MergedEnergy` type represents energy values in a merged format, and the function processes these values +accordingly to update the message vector. """ function update_message(E_bond::MergedEnergy, message::Vector, beta::Real) e11, e12, e21, e22 = E_bond.e11, E_bond.e12, E_bond.e21, E_bond.e22 @@ -244,9 +256,12 @@ Constructs a clustered Hamiltonian for a given clustered Hamiltonian with a 2-si # Returns: - `new_cl_h::LabelledGraph{MetaDiGraph}`: A new labeled graph representing the 2-site cluster Hamiltonian. - This function constructs a clustered Hamiltonian `cl_h` by applying a 2-site cluster approximation. It combines and merges vertices and edges of the original graph to create a simplified representation of the Hamiltonian. + This function constructs a clustered Hamiltonian `cl_h` by applying a 2-site cluster approximation. + It combines and merges vertices and edges of the original graph to create a simplified representation of the Hamiltonian. -The resulting `new_cl_h` graph represents the 2-site cluster Hamiltonian with simplified interactions between clusters. The energy values, projectors, and spectra associated with the new vertices and edges are computed based on the provided temperature parameter `beta`. +The resulting `new_cl_h` graph represents the 2-site cluster Hamiltonian with simplified interactions between clusters. +The energy values, projectors, and spectra associated with the new vertices and edges are computed based on +the provided temperature parameter `beta`. """ function clustered_hamiltonian_2site(cl_h::LabelledGraph{S, T}, beta::Real) where {S, T} @@ -303,9 +318,12 @@ Merge two vertices in a clustered Hamiltonian to create a single merged vertex. - `pl::AbstractVector`: The merged left projector. - `pr::AbstractVector`: The merged right projector. -This function merges two vertices in a clustered Hamiltonian graph `cl_h` to create a single merged vertex. The merging process combines projectors and energy values associated with the original vertices based on the provided temperature parameter `β`. +This function merges two vertices in a clustered Hamiltonian graph `cl_h` to create a single merged vertex. +The merging process combines projectors and energy values associated with the original vertices based on +the provided temperature parameter `β`. -The merged energy values, left projector `pl`, and right projector `pr` are computed based on the interactions between the original vertices and their respective projectors. +The merged energy values, left projector `pl`, and right projector `pr` are computed based on the interactions +between the original vertices and their respective projectors. """ function merge_vertices_cl_h(cl_h::LabelledGraph{S, T}, β::Real, node1::NTuple{3, Int64}, node2::NTuple{3, Int64} ) where {S, T} @@ -356,7 +374,8 @@ Get the local energy associated with a vertex in a clustered Hamiltonian. # Returns: - `local_energy::AbstractVector`: An abstract vector containing the local energy values associated with the specified vertex. -This function retrieves the local energy values associated with a given vertex `v` in a clustered Hamiltonian graph `cl_h`. If the vertex exists in the graph and has associated energy values, it returns those values; otherwise, it returns a vector of zeros. +This function retrieves the local energy values associated with a given vertex `v` in a clustered Hamiltonian graph `cl_h`. +If the vertex exists in the graph and has associated energy values, it returns those values; otherwise, it returns a vector of zeros. The local energy values are typically obtained from the spectrum associated with the vertex. """ @@ -377,7 +396,10 @@ Get the interaction energy between two vertices in a clustered Hamiltonian. # Returns: - `interaction_energy::AbstractMatrix`: An abstract matrix containing the interaction energy values between the specified vertices. -This function retrieves the interaction energy values between two vertices, `v` and `w`, in a clustered Hamiltonian graph `cl_h`. If there is a directed edge from `w` to `v`, it returns the corresponding energy values; if there is a directed edge from `v` to `w`, it returns the transpose of the energy values; otherwise, it returns a matrix of zeros. +This function retrieves the interaction energy values between two vertices, `v` and `w`, in a clustered Hamiltonian graph `cl_h`. +If there is a directed edge from `w` to `v`, it returns the corresponding energy values; +if there is a directed edge from `v` to `w`, it returns the transpose of the energy values; +otherwise, it returns a matrix of zeros. The interaction energy values represent the energy associated with the interaction or connection between the two vertices. """ function interaction_energy(cl_h::LabelledGraph{S, T}, v::NTuple{3, Int64}, w::NTuple{3, Int64}) where {S, T} @@ -403,7 +425,11 @@ Get the projector associated with an edge between two vertices in a clustered Ha # Returns: - `p::AbstractVector`: An abstract vector representing the projector associated with the specified edge. -This function retrieves the projector associated with an edge between two vertices, `v` and `w`, in a clustered Hamiltonian graph `cl_h`. If there is a directed edge from `w` to `v`, it returns the index of right projector (`:ipr`); if there is a directed edge from `v` to `w`, it returns the index of left projector (`:ipl`). If no edge exists between the vertices, it returns a vector of ones. +This function retrieves the projector associated with an edge between two vertices, `v` and `w`, +in a clustered Hamiltonian graph `cl_h`. +If there is a directed edge from `w` to `v`, it returns the index of right projector (`:ipr`); +if there is a directed edge from `v` to `w`, it returns the index of left projector (`:ipl`). +If no edge exists between the vertices, it returns a vector of ones. """ function projector(cl_h::LabelledGraph{S, T}, v::NTuple{N, Int64}, w::NTuple{N, Int64}) where {S, T, N} if has_edge(cl_h, w, v) @@ -439,7 +465,8 @@ Create a sparse column-compressed (CSC) matrix with specified column indices and # Returns: - `sparse_matrix::SparseMatrixCSC{R}`: A sparse column-compressed matrix with non-zero values at specified columns. -This constructor function creates a sparse column-compressed (CSC) matrix of element type `R` based on the provided column indices `p` and values. The resulting matrix has non-zero values at the specified column indices, while all other elements are zero. +This constructor function creates a sparse column-compressed (CSC) matrix of element type `R` based on the provided +column indices `p` and values. The resulting matrix has non-zero values at the specified column indices, while all other elements are zero. The `SparseCSC` constructor is useful for creating sparse matrices with specific column indices and values efficiently. """ function SparseCSC(::Type{R}, p::Vector{Int64}) where R <: Real diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index c8fd5bd..b7c6d27 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -24,7 +24,9 @@ Dict(clustered Hamiltonian coordinates -> group of spins in Ising graph) # Returns: - `clusters::Dict{L, Vertex}`: A dictionary mapping cluster identifiers to representative vertices in the Ising graph. -This function groups spins in the Ising graph into clusters based on an assignment rule. The assignment rule defines how clustered Hamiltonian coordinates correspond to clusters of spins in the Ising graph. Each cluster is represented by a vertex from the Ising graph. +This function groups spins in the Ising graph into clusters based on an assignment rule. +The assignment rule defines how clustered Hamiltonian coordinates correspond to clusters of spins in the Ising graph. +Each cluster is represented by a vertex from the Ising graph. The `split_into_clusters` function is useful for organizing and analyzing spins in complex spin systems, particularly in the context of clustered Hamiltonian. @@ -51,7 +53,10 @@ This function constructs a clustered Hamiltonian from an Ising graph by introduc # Returns: - `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. -The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by introducing a natural order in clustered Hamiltonian coordinates. It allows you to specify the number of states per cluster, a spectrum calculation function, and a cluster assignment rule, which maps Ising graph vertices to clusters. +The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by +introducing a natural order in clustered Hamiltonian coordinates. +It allows you to specify the number of states per cluster, a spectrum calculation function, +and a cluster assignment rule, which maps Ising graph vertices to clusters. This function is useful for organizing and studying spin systems in a clustered Hamiltonian framework. """ @@ -81,7 +86,9 @@ This function constructs a clustered Hamiltonian from an Ising graph by introduc # Returns: - `cl_h::LabelledGraph{MetaDiGraph}`: The clustered Hamiltonian represented as a labeled graph. -The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by introducing a natural order in clustered Hamiltonian coordinates. It allows you to specify the number of states per cluster, a spectrum calculation function, and a cluster assignment rule, which maps Ising graph vertices to clusters. +The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian +by introducing a natural order in clustered Hamiltonian coordinates. It allows you to specify the number of +states per cluster, a spectrum calculation function, and a cluster assignment rule, which maps Ising graph vertices to clusters. This function is useful for organizing and studying spin systems in a clustered Hamiltonian framework. @@ -148,9 +155,12 @@ This function constructs a clustered Hamiltonian from an Ising graph by introduc # Returns: - `cl_h::LabelledGraph{MetaDiGraph}`: The clustered Hamiltonian represented as a labeled graph. -The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by introducing a natural order in clustered Hamiltonian coordinates. You can optionally specify a spectrum calculation function and a cluster assignment rule, which maps Ising graph vertices to clusters. +The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian +by introducing a natural order in clustered Hamiltonian coordinates. +You can optionally specify a spectrum calculation function and a cluster assignment rule, which maps Ising graph vertices to clusters. -If you want to specify custom cluster sizes, use the alternative version of this function by passing a `Dict{T, Int}` containing the number of states per cluster as `num_states_cl`. +If you want to specify custom cluster sizes, use the alternative version of this function by +passing a `Dict{T, Int}` containing the number of states per cluster as `num_states_cl`. This function is useful for organizing and studying spin systems in a clustered Hamiltonian framework. """ @@ -167,11 +177,13 @@ $(TYPEDSIGNATURES) Reveal ranks and energies in a specified order. -This function calculates and reveals the ranks and energies of a set of states in either the 'PE' (Projector Energy) or 'EP' (Energy Projector) order. +This function calculates and reveals the ranks and energies of a set of states in either the +'PE' (Projector Energy) or 'EP' (Energy Projector) order. # Arguments: - `energy`: The energy values of states. -- `order::Symbol`: The order in which to reveal the ranks and energies. It can be either `:PE` for 'Projector Energy)' order (default) or `:EP` for 'Energy Projector' order. +- `order::Symbol`: The order in which to reveal the ranks and energies. +It can be either `:PE` for 'Projector Energy)' order (default) or `:EP` for 'Energy Projector' order. # Returns: - If `order` is `:PE`, the function returns a tuple `(P, E)` where: @@ -196,7 +208,8 @@ TODO: check the order consistency over external packages. Decode a clustered Hamiltonian state into Ising graph spin values. -This function decodes a state from a clustered Hamiltonian into Ising graph spin values and returns a dictionary mapping each Ising graph vertex to its corresponding spin value. +This function decodes a state from a clustered Hamiltonian into Ising graph spin values and +returns a dictionary mapping each Ising graph vertex to its corresponding spin value. # Arguments: - `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. @@ -205,7 +218,8 @@ This function decodes a state from a clustered Hamiltonian into Ising graph spin # Returns: - `spin_values::Dict{Int, Int}`: A dictionary mapping each Ising graph vertex to its corresponding spin value. -This function assumes that the state has the same order as the vertices in the clustered Hamiltonian. It decodes the state consistently based on the cluster assignments and spectra of the clustered Hamiltonian. +This function assumes that the state has the same order as the vertices in the clustered Hamiltonian. +It decodes the state consistently based on the cluster assignments and spectra of the clustered Hamiltonian. """ function decode_clustered_hamiltonian_state(cl_h::LabelledGraph{S, T}, state::Vector{Int}) where {S, T} ret = Dict{Int, Int}() @@ -225,7 +239,8 @@ $(TYPEDSIGNATURES) Calculate the energy of a clustered Hamiltonian state. -This function calculates the energy of a given state in a clustered Hamiltonian. The state is represented as a dictionary mapping each Ising graph vertex to its corresponding spin value. +This function calculates the energy of a given state in a clustered Hamiltonian. +The state is represented as a dictionary mapping each Ising graph vertex to its corresponding spin value. # Arguments: - `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. @@ -234,7 +249,9 @@ This function calculates the energy of a given state in a clustered Hamiltonian. # Returns: - `en_cl_h::Float64`: The energy of the state in the clustered Hamiltonian. -This function computes the energy by summing the energies associated with individual clusters and the interaction energies between clusters. It takes into account the cluster spectra and projectors stored in the clustered Hamiltonian. +This function computes the energy by summing the energies associated with individual +clusters and the interaction energies between clusters. +It takes into account the cluster spectra and projectors stored in the clustered Hamiltonian. """ function energy(cl_h::LabelledGraph{S, T}, σ::Dict{T, Int}) where {S, T} en_cl_h = 0.0 @@ -265,7 +282,9 @@ This function computes the interaction energy between two specified nodes in a c # Returns: - `int_eng::AbstractMatrix{T}`: The interaction energy matrix between the specified sites. -The function checks if there is an interaction edge between the two sites (i, j) in both directions (i -> j and j -> i). If such edges exist, it retrieves the interaction energy matrix, projectors, and calculates the interaction energy. If no interaction edge is found, it returns a zero matrix. +The function checks if there is an interaction edge between the two sites (i, j) in both directions (i -> j and j -> i). +If such edges exist, it retrieves the interaction energy matrix, projectors, and calculates the interaction energy. +If no interaction edge is found, it returns a zero matrix. """ function energy_2site(cl_h::LabelledGraph{S, T}, i::Int, j::Int) where {S, T} # matrix of interaction energies between two nodes @@ -305,7 +324,9 @@ This function computes the bond energy between two specified clusters (cluster n # Returns: - `energies::AbstractVector{T}`: The bond energy vector between the two clusters for the specified index. -The function checks if there is an edge between the two clusters (u -> v and v -> u). If such edges exist, it retrieves the bond energy matrix and projectors and calculates the bond energy. If no bond edge is found, it returns a zero vector. +The function checks if there is an edge between the two clusters (u -> v and v -> u). +If such edges exist, it retrieves the bond energy matrix and projectors and calculates the bond energy. +If no bond edge is found, it returns a zero vector. """ function bond_energy( cl_h::LabelledGraph{S, T}, @@ -367,7 +388,9 @@ This function computes the exact conditional probability of a specified target s # Returns: - `prob::Float64`: The exact conditional probability of the target state. -The function generates all possible states for the clusters in the clustered Hamiltonian, calculates their energies, and computes the probability distribution based on the given inverse temperature parameter. It then calculates the conditional probability of the specified target state by summing the probabilities of states that match the target state. +The function generates all possible states for the clusters in the clustered Hamiltonian, +calculates their energies, and computes the probability distribution based on the given inverse temperature parameter. +It then calculates the conditional probability of the specified target state by summing the probabilities of states that match the target state. """ function exact_cond_prob(clustered_hamiltonian::LabelledGraph{S, T}, beta, target_state::Dict) where {S, T} # TODO: Not going to work without PoolOfProjectors diff --git a/src/ising.jl b/src/ising.jl index 2b2639e..9672617 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -25,18 +25,22 @@ $(TYPEDSIGNATURES) Create an Ising graph from interaction data. -This function creates an Ising graph from interaction data provided in the form of an `inst` argument. The Ising graph represents a system of spins, where each spin is associated with a vertex, and interactions between spins are represented as edges with corresponding weights. +This function creates an Ising graph from interaction data provided in the form of an `inst` argument. +The Ising graph represents a system of spins, where each spin is associated with a vertex, and interactions between spins are represented as edges with corresponding weights. # Arguments: - `::Type{T}`: The type of the edge weights, typically `Float64` or `Float32`. -- `inst::Instance`: Interaction data, which can be either a file path to a CSV file or a collection of triples `(i, j, J)` representing interactions between spins, where `i` and `j` are spin indices, and `J` is the interaction strength. +- `inst::Instance`: Interaction data, which can be either a file path to a CSV file or a collection of triples `(i, j, J)` +representing interactions between spins, where `i` and `j` are spin indices, and `J` is the interaction strength. - `scale::Real`: A scaling factor applied to interaction strengths (default is 1). - `rank_override::Dict`: A dictionary specifying the rank (number of states) for each vertex. If not provided, a default rank of 2 is used for all vertices. # Returns: - `ig::IsingGraph{T}`: The Ising graph representing the spin system. -The function reads interaction data and constructs an Ising graph `ig`. It assigns interaction strengths to edges between spins and optionally scales them by the `scale` factor. The `rank_override` dictionary can be used to specify the rank (number of states) for individual vertices, allowing customization of the Ising model. +The function reads interaction data and constructs an Ising graph `ig`. +It assigns interaction strengths to edges between spins and optionally scales them by the `scale` factor. +The `rank_override` dictionary can be used to specify the rank (number of states) for individual vertices, allowing customization of the Ising model. Convention: H = scale * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) """ function ising_graph(::Type{T}, inst::Instance; scale::Real=1, rank_override::Dict=Dict{Int, Int}()) where T @@ -77,7 +81,8 @@ $(TYPEDSIGNATURES) Return the coupling strengths between vertices of an Ising graph. -This function computes and returns the coupling strengths (interaction energies) between pairs of vertices in an Ising graph `ig`. The coupling strengths are represented as a matrix, where each element `(i, j)` corresponds to the interaction energy between vertex `i` and vertex `j`. +This function computes and returns the coupling strengths (interaction energies) between pairs of vertices in an Ising graph `ig`. +The coupling strengths are represented as a matrix, where each element `(i, j)` corresponds to the interaction energy between vertex `i` and vertex `j`. # Arguments: - `ig::IsingGraph{T}`: The Ising graph representing a system of spins with associated interaction strengths. @@ -103,7 +108,10 @@ $(TYPEDSIGNATURES) Return the dense adjacency matrix between clusters of vertices in an Ising graph. -This function computes and returns the dense adjacency matrix `J` between clusters of vertices represented by two Ising graphs, `cl1` and `cl2`, within the context of the larger Ising graph `ig`. The adjacency matrix represents the interaction strengths between clusters of vertices, where each element `(i, j)` corresponds to the interaction strength between cluster `i` in `cl1` and cluster `j` in `cl2`. +This function computes and returns the dense adjacency matrix `J` between clusters of vertices represented by two +Ising graphs, `cl1` and `cl2`, within the context of the larger Ising graph `ig`. +The adjacency matrix represents the interaction strengths between clusters of vertices, +where each element `(i, j)` corresponds to the interaction strength between cluster `i` in `cl1` and cluster `j` in `cl2`. # Arguments: - `ig::IsingGraph{T}`: The Ising graph representing a system of spins with associated interaction strengths. @@ -114,7 +122,8 @@ This function computes and returns the dense adjacency matrix `J` between cluste - `outer_edges::Vector{LabelledEdge}`: A vector of labeled edges representing the interactions between clusters. - `J::Matrix{T}`: A dense adjacency matrix representing interaction strengths between clusters. -The function first identifies the outer edges that connect vertices between the two clusters in the context of the larger Ising graph `ig`. It then computes the interaction strengths associated with these outer edges and populates the dense adjacency matrix `J` accordingly. +The function first identifies the outer edges that connect vertices between the two clusters in the context of the larger Ising graph `ig`. +It then computes the interaction strengths associated with these outer edges and populates the dense adjacency matrix `J` accordingly. """ function inter_cluster_edges(ig::IsingGraph{T}, cl1::IsingGraph{T}, cl2::IsingGraph{T}) where T outer_edges = [LabelledEdge(i, j) for i ∈ vertices(cl1), j ∈ vertices(cl2) if has_edge(ig, i, j)] @@ -132,7 +141,9 @@ $(TYPEDSIGNATURES) Used only in MPS_search, would be obsolete if MPS_search uses QMps. Remove non-existing spins from an Ising graph. -This function removes non-existing spins from the given Ising graph `ig`. Non-existing spins are those that have zero degree (no connections to other spins) and also have an external magnetic field (`h`) that is not approximately equal to zero within the specified tolerance `atol`. +This function removes non-existing spins from the given Ising graph `ig`. +Non-existing spins are those that have zero degree (no connections to other spins) and also have an external +magnetic field (`h`) that is not approximately equal to zero within the specified tolerance `atol`. # Arguments: - `ig::IsingGraph`: The Ising graph to be pruned. diff --git a/src/lattice.jl b/src/lattice.jl index e36df5a..55b7e1d 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -15,7 +15,8 @@ $(TYPEDSIGNATURES) Create a mapping from clustered Hamiltonian coordinates to a super square lattice arrangement. Variable number of Ising graph -> Factor graph coordinate system -This function generates a mapping that relates clustered Hamiltonian coordinates to a super square lattice arrangement. The super square lattice is defined by the size of five dimensions: `(m, um, n, un, t)`. +This function generates a mapping that relates clustered Hamiltonian coordinates to a super square lattice arrangement. +The super square lattice is defined by the size of five dimensions: `(m, um, n, un, t)`. # Arguments: - `size::NTuple{5, Int}`: A tuple specifying the size of the super square lattice in five dimensions: `(m, um, n, un, t)`. @@ -23,7 +24,8 @@ This function generates a mapping that relates clustered Hamiltonian coordinates # Returns: - `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding lattice coordinates. -The `size` tuple represents the dimensions of the super square lattice. The function creates a dictionary where clustered Hamiltonian coordinates are associated with their corresponding lattice coordinates. +The `size` tuple represents the dimensions of the super square lattice. The function creates a dictionary where +clustered Hamiltonian coordinates are associated with their corresponding lattice coordinates. """ function super_square_lattice(size::NTuple{5, Int}) m, um, n, un, t = size @@ -36,7 +38,8 @@ $(TYPEDSIGNATURES) Create a mapping from clustered Hamiltonian coordinates to a simplified super square lattice arrangement. -This function generates a mapping that relates clustered Hamiltonian coordinates to a simplified super square lattice arrangement. The simplified super square lattice is defined by the size of three dimensions: `(m, n, t)`. +This function generates a mapping that relates clustered Hamiltonian coordinates to a simplified super square lattice arrangement. +The simplified super square lattice is defined by the size of three dimensions: `(m, n, t)`. # Arguments: - `size::NTuple{3, Int}`: A tuple specifying the size of the simplified super square lattice in three dimensions: `(m, n, t)`. @@ -44,7 +47,8 @@ This function generates a mapping that relates clustered Hamiltonian coordinates # Returns: - `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding lattice coordinates. -The `size` tuple represents the dimensions of the simplified super square lattice. The function internally adds the required dimensions `(1, 1)` to make it compatible with the `super_square_lattice` function, which deals with five dimensions. +The `size` tuple represents the dimensions of the simplified super square lattice. +The function internally adds the required dimensions `(1, 1)` to make it compatible with the `super_square_lattice` function, which deals with five dimensions. """ function super_square_lattice(size::NTuple{3, Int}) m, n, t = size @@ -58,7 +62,8 @@ $(TYPEDSIGNATURES) Create a mapping from clustered Hamiltonian coordinates to Pegasus lattice coordinates. -This function generates a mapping that relates clustered Hamiltonian coordinates to Pegasus lattice coordinates based on the specified size of the Pegasus lattice in three dimensions: `(m, n, t)`. +This function generates a mapping that relates clustered Hamiltonian coordinates to Pegasus lattice coordinates +based on the specified size of the Pegasus lattice in three dimensions: `(m, n, t)`. # Arguments: - `size::NTuple{3, Int}`: A tuple specifying the size of the Pegasus lattice in three dimensions: `(m, n, t)`. @@ -66,7 +71,8 @@ This function generates a mapping that relates clustered Hamiltonian coordinates # Returns: - `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding Pegasus lattice coordinates. -The Pegasus lattice is a specialized lattice used in quantum computing, and this function allows you to convert between clustered Hamiltonian coordinates and Pegasus lattice coordinates. +The Pegasus lattice is a specialized lattice used in quantum computing, and this function allows you to convert +between clustered Hamiltonian coordinates and Pegasus lattice coordinates. """ function pegasus_lattice(size::NTuple{3, Int}) m, n, t = size @@ -132,7 +138,8 @@ $(TYPEDSIGNATURES) Create a mapping from clustered Hamiltonian coordinates to Zephyr lattice coordinates. -This function generates a mapping that relates clustered Hamiltonian coordinates to Zephyr lattice coordinates based on the specified size of the Zephyr lattice in three dimensions: `(m, n, t)`. +This function generates a mapping that relates clustered Hamiltonian coordinates to Zephyr lattice +coordinates based on the specified size of the Zephyr lattice in three dimensions: `(m, n, t)`. # Arguments: - `size::NTuple{3, Int}`: A tuple specifying the size of the Zephyr lattice in three dimensions: `(m, n, t)`. @@ -140,7 +147,8 @@ This function generates a mapping that relates clustered Hamiltonian coordinates # Returns: - `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding Zephyr lattice coordinates. -The Zephyr lattice is a specialized lattice used in quantum computing, and this function allows you to convert between clustered Hamiltonian coordinates and Zephyr lattice coordinates. +The Zephyr lattice is a specialized lattice used in quantum computing, and this function allows you to +convert between clustered Hamiltonian coordinates and Zephyr lattice coordinates. """ function zephyr_lattice(size::NTuple{3, Int}) m, n, t = size diff --git a/src/projectors.jl b/src/projectors.jl index ec16fcd..5b6f0cf 100644 --- a/src/projectors.jl +++ b/src/projectors.jl @@ -9,16 +9,20 @@ const Proj{T} = Union{Vector{T}, CuArray{T, 1}} """ $(TYPEDSIGNATURES) -`PoolOfProjectors` is a data structure for managing projectors associated with Ising model sites. It allows efficient storage and retrieval of projectors based on their indices and provides support for different computational devices. - - # Fields: - - `data::Dict{Symbol, Dict{Int, Proj{T}}}`: A dictionary that stores projectors associated with different computational devices (`:CPU`, `:GPU`, etc.). The inner dictionary maps site indices to projectors. - - `default_device::Symbol`: A symbol representing the default computational device for projectors in the pool. - - `sizes::Dict{Int, Int}`: A dictionary that maps site indices to the maximum projector size for each site. +`PoolOfProjectors` is a data structure for managing projectors associated with Ising model sites. +It allows efficient storage and retrieval of projectors based on their indices and provides support for different computational devices. + +# Fields: +- `data::Dict{Symbol, Dict{Int, Proj{T}}}`: A dictionary that stores projectors associated with different +computational devices (`:CPU`, `:GPU`, etc.). The inner dictionary maps site indices to projectors. +- `default_device::Symbol`: A symbol representing the default computational device for projectors in the pool. +- `sizes::Dict{Int, Int}`: A dictionary that maps site indices to the maximum projector size for each site. - # Constructors: - - `PoolOfProjectors(data::Dict{Int, Dict{Int, Vector{T}}}) where T`: Create a `PoolOfProjectors` with initial data for projectors. The data is provided as a dictionary that maps site indices to projectors stored in different computational devices. The `sizes` dictionary is automatically populated based on the maximum projector size for each site. - - `PoolOfProjectors{T}() where T`: Create an empty `PoolOfProjectors` with no projectors initially stored. +# Constructors: +- `PoolOfProjectors(data::Dict{Int, Dict{Int, Vector{T}}}) where T`: Create a `PoolOfProjectors` with initial data for projectors. +The data is provided as a dictionary that maps site indices to projectors stored in different computational devices. +The `sizes` dictionary is automatically populated based on the maximum projector size for each site. +- `PoolOfProjectors{T}() where T`: Create an empty `PoolOfProjectors` with no projectors initially stored. """ struct PoolOfProjectors{T <: Integer} data::Dict{Symbol, Dict{Int, Proj{T}}} @@ -69,7 +73,8 @@ TODO This is version for only one GPU Retrieve or create a projector from the `PoolOfProjectors` associated with a specific device. -This function retrieves a projector from the `PoolOfProjectors` if it already exists. If the projector does not exist in the pool, it creates a new one and stores it for future use on the specified computational device. +This function retrieves a projector from the `PoolOfProjectors` if it already exists. +If the projector does not exist in the pool, it creates a new one and stores it for future use on the specified computational device. # Arguments: - `lp::PoolOfProjectors{T}`: The `PoolOfProjectors` object containing projectors. @@ -102,7 +107,9 @@ $(TYPEDSIGNATURES) Add a projector to the `PoolOfProjectors` and associate it with an index. -This function adds a projector `p` to the `PoolOfProjectors`. The `PoolOfProjectors` stores projectors based on their computational device (e.g., CPU or GPU) and assigns a unique index to each projector. The index can be used to retrieve the projector later using `get_projector!`. +This function adds a projector `p` to the `PoolOfProjectors`. +The `PoolOfProjectors` stores projectors based on their computational device (e.g., CPU or GPU) and assigns a unique index to each projector. +The index can be used to retrieve the projector later using `get_projector!`. # Arguments: - `lp::PoolOfProjectors{T}`: The `PoolOfProjectors` object to which the projector should be added. diff --git a/src/spectrum.jl b/src/spectrum.jl index 78c465d..d38df75 100644 --- a/src/spectrum.jl +++ b/src/spectrum.jl @@ -69,7 +69,8 @@ $(TYPEDSIGNATURES) Calculates the energy of a state in an Ising graph. -This function calculates the energy of a given state in the context of an Ising graph. The energy is computed based on the interactions between spins and their associated biases. +This function calculates the energy of a given state in the context of an Ising graph. +The energy is computed based on the interactions between spins and their associated biases. # Arguments: - `σ::AbstractArray{State}`: An array representing the state of spins in the Ising graph. @@ -88,7 +89,8 @@ $(TYPEDSIGNATURES) Calculates the energy of a state in an Ising graph. -This function computes the energy of a given state in the context of an Ising graph. The energy is calculated based on the interactions between spins and their associated biases. +This function computes the energy of a given state in the context of an Ising graph. +The energy is calculated based on the interactions between spins and their associated biases. # Arguments: - `ig::IsingGraph{T}`: The Ising graph defining the interactions and biases. @@ -117,7 +119,8 @@ $(TYPEDSIGNATURES) Generates the energy spectrum for an Ising graph. -This function computes the energy spectrum (energies and corresponding states) for a given Ising graph. The energy spectrum represents all possible energy levels and their associated states in the Ising graph. +This function computes the energy spectrum (energies and corresponding states) for a given Ising graph. +The energy spectrum represents all possible energy levels and their associated states in the Ising graph. # Arguments: - `ig::IsingGraph{T}`: The Ising graph for which the energy spectrum is generated. @@ -145,7 +148,8 @@ $(TYPEDSIGNATURES) Computes the Gibbs tensor for an Ising graph at a given inverse temperature. -This function calculates the Gibbs tensor for an Ising graph at a specified inverse temperature (β). The Gibbs tensor represents the conditional probabilities of states given the inverse temperature and the Ising graph. +This function calculates the Gibbs tensor for an Ising graph at a specified inverse temperature (β). +The Gibbs tensor represents the conditional probabilities of states given the inverse temperature and the Ising graph. # Arguments: - `ig::IsingGraph{T}`: The Ising graph for which the Gibbs tensor is computed. diff --git a/src/truncate.jl b/src/truncate.jl index db298d8..1ae5f63 100644 --- a/src/truncate.jl +++ b/src/truncate.jl @@ -113,7 +113,8 @@ $(TYPEDSIGNATURES) Select a specified number of best states based on energy. -This function selects a specified number of best states from a list of energies based on energy values in two nodes of clustered hamiltonian. It fine-tunes the selection to ensure that the resulting states have the expected number. +This function selects a specified number of best states from a list of energies based on energy values in two nodes of clustered hamiltonian. +It fine-tunes the selection to ensure that the resulting states have the expected number. # Arguments: - `E::Vector{Real}`: A vector of energy values. @@ -121,7 +122,8 @@ This function selects a specified number of best states from a list of energies - `num_states::Int`: The desired number of states to select. # Returns: -- `Tuple{Vector{Int}, Vector{Int}}`: A tuple containing two vectors of indices, `ind1` and `ind2`, which represent the selected states for two nodes of a clustered Hamiltonian. +- `Tuple{Vector{Int}, Vector{Int}}`: A tuple containing two vectors of indices, `ind1` and `ind2`, +which represent the selected states for two nodes of a clustered Hamiltonian. """ function select_numstate_best(E, sx, num_states) low, high = 1, min(num_states, length(E)) From b9845226ab3c54807aceea3d7da2433af3d11d11 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Fri, 13 Oct 2023 10:10:46 +0200 Subject: [PATCH 181/218] corrected the function names --- src/lattice.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/lattice.jl b/src/lattice.jl index 55b7e1d..298e160 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -87,7 +87,7 @@ function pegasus_lattice(size::NTuple{3, Int}) end # TODO masoud / tomek should be removed from function names -function pegasus_lattice_masoud(size::NTuple{3, Int}) +function pegasus_lattice_alternative(size::NTuple{3, Int}) m, n, t = size old = LinearIndices((1:8*t, 1:n, 1:m)) map = Dict( @@ -99,7 +99,7 @@ function pegasus_lattice_masoud(size::NTuple{3, Int}) map end -function pegasus_lattice_tomek(size::NTuple{3, Int}) +function pegasus_lattice_old_numering(size::NTuple{3, Int}) m, n, t = size old = LinearIndices((1:8*t, 1:n, 1:m)) map = Dict( From 0e420f4a5c6c6ea392ca1fd9b9cf0283442f3962 Mon Sep 17 00:00:00 2001 From: Bartek Date: Fri, 27 Oct 2023 09:12:30 +0000 Subject: [PATCH 182/218] clean up toml --- Project.toml | 7 ++++--- src/ising.jl | 22 +++++++++++----------- 2 files changed, 15 insertions(+), 14 deletions(-) diff --git a/Project.toml b/Project.toml index 5f14176..5f411ef 100644 --- a/Project.toml +++ b/Project.toml @@ -5,24 +5,25 @@ version = "0.2.3" [deps] CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b" +CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae" LabelledGraphs = "605abd48-4d17-4660-b914-d4df33194460" LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2" MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5" -SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf" NNlibCUDA = "a00861dc-f156-4864-bf3c-e6376f28a68d" -CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" +SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf" +TensorCast = "02d47bb6-7ce6-556a-be16-bb1710789e2b" [compat] CSV = "0.8" DocStringExtensions = "0.8" LabelledGraphs = "0.3.2" LightGraphs = "1.3" +MKL = "0.4.2" MetaGraphs = "0.6" julia = "1.5, 1.6, 1.7" -MKL = "0.4.2" [extras] Logging = "56ddb016-857b-54e1-b83d-db4d58db5568" diff --git a/src/ising.jl b/src/ising.jl index 9672617..50f0b6a 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -25,12 +25,12 @@ $(TYPEDSIGNATURES) Create an Ising graph from interaction data. -This function creates an Ising graph from interaction data provided in the form of an `inst` argument. +This function creates an Ising graph from interaction data provided in the form of an `inst` argument. The Ising graph represents a system of spins, where each spin is associated with a vertex, and interactions between spins are represented as edges with corresponding weights. # Arguments: - `::Type{T}`: The type of the edge weights, typically `Float64` or `Float32`. -- `inst::Instance`: Interaction data, which can be either a file path to a CSV file or a collection of triples `(i, j, J)` +- `inst::Instance`: Interaction data, which can be either a file path to a CSV file or a collection of triples `(i, j, J)` representing interactions between spins, where `i` and `j` are spin indices, and `J` is the interaction strength. - `scale::Real`: A scaling factor applied to interaction strengths (default is 1). - `rank_override::Dict`: A dictionary specifying the rank (number of states) for each vertex. If not provided, a default rank of 2 is used for all vertices. @@ -38,8 +38,8 @@ representing interactions between spins, where `i` and `j` are spin indices, and # Returns: - `ig::IsingGraph{T}`: The Ising graph representing the spin system. -The function reads interaction data and constructs an Ising graph `ig`. -It assigns interaction strengths to edges between spins and optionally scales them by the `scale` factor. +The function reads interaction data and constructs an Ising graph `ig`. +It assigns interaction strengths to edges between spins and optionally scales them by the `scale` factor. The `rank_override` dictionary can be used to specify the rank (number of states) for individual vertices, allowing customization of the Ising model. Convention: H = scale * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) """ @@ -81,7 +81,7 @@ $(TYPEDSIGNATURES) Return the coupling strengths between vertices of an Ising graph. -This function computes and returns the coupling strengths (interaction energies) between pairs of vertices in an Ising graph `ig`. +This function computes and returns the coupling strengths (interaction energies) between pairs of vertices in an Ising graph `ig`. The coupling strengths are represented as a matrix, where each element `(i, j)` corresponds to the interaction energy between vertex `i` and vertex `j`. # Arguments: @@ -108,9 +108,9 @@ $(TYPEDSIGNATURES) Return the dense adjacency matrix between clusters of vertices in an Ising graph. -This function computes and returns the dense adjacency matrix `J` between clusters of vertices represented by two -Ising graphs, `cl1` and `cl2`, within the context of the larger Ising graph `ig`. -The adjacency matrix represents the interaction strengths between clusters of vertices, +This function computes and returns the dense adjacency matrix `J` between clusters of vertices represented by two +Ising graphs, `cl1` and `cl2`, within the context of the larger Ising graph `ig`. +The adjacency matrix represents the interaction strengths between clusters of vertices, where each element `(i, j)` corresponds to the interaction strength between cluster `i` in `cl1` and cluster `j` in `cl2`. # Arguments: @@ -122,7 +122,7 @@ where each element `(i, j)` corresponds to the interaction strength between clus - `outer_edges::Vector{LabelledEdge}`: A vector of labeled edges representing the interactions between clusters. - `J::Matrix{T}`: A dense adjacency matrix representing interaction strengths between clusters. -The function first identifies the outer edges that connect vertices between the two clusters in the context of the larger Ising graph `ig`. +The function first identifies the outer edges that connect vertices between the two clusters in the context of the larger Ising graph `ig`. It then computes the interaction strengths associated with these outer edges and populates the dense adjacency matrix `J` accordingly. """ function inter_cluster_edges(ig::IsingGraph{T}, cl1::IsingGraph{T}, cl2::IsingGraph{T}) where T @@ -141,8 +141,8 @@ $(TYPEDSIGNATURES) Used only in MPS_search, would be obsolete if MPS_search uses QMps. Remove non-existing spins from an Ising graph. -This function removes non-existing spins from the given Ising graph `ig`. -Non-existing spins are those that have zero degree (no connections to other spins) and also have an external +This function removes non-existing spins from the given Ising graph `ig`. +Non-existing spins are those that have zero degree (no connections to other spins) and also have an external magnetic field (`h`) that is not approximately equal to zero within the specified tolerance `atol`. # Arguments: From 9a0577aa76ec41fcdfc5492a80c15c2772a21a45 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Wed, 15 Nov 2023 14:31:49 +0100 Subject: [PATCH 183/218] added function for loading openGM images --- src/utils.jl | 86 +++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 85 insertions(+), 1 deletion(-) diff --git a/src/utils.jl b/src/utils.jl index 16166a2..d043242 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -1,8 +1,11 @@ export zephyr_to_linear, - unique_neighbors + unique_neighbors, + load_openGM import Base.Prehashed +using HDF5 + """ $(TYPEDSIGNATURES) @@ -88,3 +91,84 @@ unique_neighbors(ig::LabelledGraph, i::Int) = filter(j -> j > i, neighbors(ig, i (@nref $N A d->d == dim ? sort!(uniquerows) : (axes(A, d))), indexin(uniquerow, uniquerows) end end + +""" +$(TYPEDSIGNATURES) +Loads some factored graphs written in openGM format. Assumes rectangular lattice. + +Args: + file_name (str): a path to file with factor graph in openGM format. + ints Nx, Ny: it is assumed that graph if forming an :math:N_x \times N_y lattice with + nearest-neighbour interactions only. + +Returns: + dictionary with factors and funcitons defining the energy functional. +""" +function load_openGM(fname::String, Nx::Integer, Ny::Integer) + file = h5open(fname, "r") + + file_keys = collect(keys(read(file))) + data = read(file[file_keys[1]]) + H = collect(Int64, data["header"]) + F = Array{Int64}(data["factors"]) + J = Array{Int64}(data["function-id-16000"]["indices"]) + V = Array{Real}(data["function-id-16000"]["values"]) + N = Array{Int64}(data["numbers-of-states"]) + + F = reverse(F) + factors = Dict() + + while length(F) > 0 + f1 = pop!(F) + z1 = pop!(F) + nn = pop!(F) + n = [] + + for _ in 1:nn + tt = pop!(F) + ny, nx = divrem(tt, Nx) + push!(n, ny, nx) + end + + if length(n) == 4 + if abs(n[1] - n[3]) + abs(n[2] - n[4]) != 1 + throw(ErrorException("Not nearest neighbour")) + end + end + + if length(n) == 2 + if (n[1] >= Ny) || (n[2] >= Nx) + throw(ErrorException("Wrong size")) + end + end + + factors[tuple(n...)] = f1 + + if z1 != 0 + throw(ErrorException("Something wrong with the expected convention.")) + end + end + + J = reverse(J) + functions = Dict() + ii = -1 + lower = 0 + + while length(J) > 0 + ii += 1 + nn = pop!(J) + n = [] + + for _ in 1:nn + push!(n, pop!(J)) + end + + upper = lower + prod(n) + functions[ii] = reshape(V[lower + 1:upper], reverse(n)...)' + + lower = upper + end + + result = Dict("fun" => functions, "fac" => factors, "N" => reshape(N, (Ny, Nx)), "Nx" => Nx, "Ny" => Ny) + result +end \ No newline at end of file From c6030cd91fceb96d4ece4480ebc697edef1754f7 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Thu, 16 Nov 2023 17:51:52 +0100 Subject: [PATCH 184/218] WIP rmf --- Project.toml | 5 +- examples/penguin-small.h5 | Bin 0 -> 15346712 bytes examples/temp.jl | 116 ++++++++++++++++++++++++++++++++++++++ src/SpinGlassNetworks.jl | 1 + 4 files changed, 120 insertions(+), 2 deletions(-) create mode 100644 examples/penguin-small.h5 create mode 100644 examples/temp.jl diff --git a/Project.toml b/Project.toml index 5f411ef..3de7d07 100644 --- a/Project.toml +++ b/Project.toml @@ -7,12 +7,13 @@ version = "0.2.3" CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b" CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae" +HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f" LabelledGraphs = "605abd48-4d17-4660-b914-d4df33194460" LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2" MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5" -NNlibCUDA = "a00861dc-f156-4864-bf3c-e6376f28a68d" +NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd" SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf" TensorCast = 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zgWEefxV?Xa+q*Wny;p 0 + f1 = pop!(F) + z1 = pop!(F) + nn = pop!(F) + n = [] + + for _ in 1:nn + tt = pop!(F) + ny, nx = divrem(tt, Nx) + push!(n, ny, nx) + end + + if length(n) == 4 + if abs(n[1] - n[3]) + abs(n[2] - n[4]) != 1 + throw(Exception("Not nearest neighbour")) + end + end + + if length(n) == 2 + if (n[1] >= Ny) || (n[2] >= Nx) + throw(Exception("Wrong size")) + end + end + + factors[tuple(n...)] = f1 + + if z1 != 0 + throw(Exception("Something wrong with the expected convention.")) + end + end + + J = reverse(J) + functions = Dict() + ii = -1 + lower = 0 + + while length(J) > 0 + ii += 1 + nn = pop!(J) + n = [] + + for _ in 1:nn + push!(n, pop!(J)) + end + + upper = lower + prod(n) + functions[ii] = reshape(V[lower + 1:upper], reverse(n)...)' + + lower = upper + end + + result = Dict("fun" => functions, "fac" => factors, "N" => reshape(N, (Ny, Nx)), "Nx" => Nx, "Ny" => Ny) + result +end + +function energy_rmf() + +end + +function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 320) + loaded_rmf = load_openGM(fname, Nx, Ny) + functions = loaded_rmf["fun"] + factors = loaded_rmf["fac"] + N = loaded_rmf["N"] + println(size(N)) + node_factors = Dict() + edge_factors = Dict() + + for index in keys(factors) + if length(index) == 4 + push!(edge_factors, index=>factors[index]) + else + push!(node_factors, index=>factors[index]) + end + end + println(length(node_factors)) + println((0,0) in collect(keys(node_factors))) + g = grid((Nx,Ny)) + clusters = super_square_lattice((Nx, Ny, 1)) + cl_h = LabelledGraph{MetaDiGraph}(sort(collect(values(clusters)))) + for v ∈ cl_h.labels + x, y = v + sp = Spectrum([node_factors[(y-1, x-1)]], Array([collect(1:N[y, x])]), Vector{Int}([])) + set_props!(cl_h, v, Dict(:cluster => v, :spectrum => sp)) + end + + cl_h +end + + +x, y = 240, 320 +filename = "/home/tsmierzchalski/.julia/dev/SpinGlassNetworks/examples/penguin-small.h5" + + +cf = clustered_hamiltonian(filename, x, y) diff --git a/src/SpinGlassNetworks.jl b/src/SpinGlassNetworks.jl index b019c09..398fcc9 100644 --- a/src/SpinGlassNetworks.jl +++ b/src/SpinGlassNetworks.jl @@ -7,6 +7,7 @@ module SpinGlassNetworks using LinearAlgebra, MKL using Base.Cartesian using SparseArrays + using HDF5 using CUDA, CUDA.CUSPARSE import Base.Prehashed From 4008b7b5545a8d5f304d80db0300697b09f4bc3c Mon Sep 17 00:00:00 2001 From: annamariadziubyna <73058800+annamariadziubyna@users.noreply.github.com> Date: Fri, 17 Nov 2023 07:34:33 +0100 Subject: [PATCH 185/218] add the docs --- docs/make.jl | 7 ++- docs/src/api.md | 12 ---- docs/src/bp.md | 9 +++ docs/src/clh.md | 25 +++++++++ docs/src/ising.md | 25 +++++++++ docs/src/lattice.md | 90 ++++++++++++++++++++++++++++++ docs/src/userguide.md | 124 +----------------------------------------- 7 files changed, 156 insertions(+), 136 deletions(-) create mode 100644 docs/src/bp.md create mode 100644 docs/src/clh.md create mode 100644 docs/src/ising.md create mode 100644 docs/src/lattice.md diff --git a/docs/make.jl b/docs/make.jl index fbb6101..c54d524 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -1,9 +1,12 @@ using Documenter, SpinGlassNetworks _pages = [ - "Introduction" => "index.md", "User guide" => "userguide.md", - "API Reference" => "api.md" + "Lattice geometries" => "lattice.md", + "Ising graph" => "ising.md", + "Clustered hamiltonian" => "clh.md", + "Local dimensional reduction" => "bp.md", + "API Reference for auxiliary functions" => "api.md" ] # ============================ diff --git a/docs/src/api.md b/docs/src/api.md index 3e134c7..342a2fe 100644 --- a/docs/src/api.md +++ b/docs/src/api.md @@ -8,7 +8,6 @@ CurrentModule = SpinGlassNetworks ## Ising Graphs ```@docs -ising_graph inter_cluster_edges prune couplings @@ -17,7 +16,6 @@ couplings ## Clustered Hamiltonian ```@docs split_into_clusters -clustered_hamiltonian decode_clustered_hamiltonian_state rank_reveal energy @@ -28,22 +26,13 @@ exact_cond_prob truncate_clustered_hamiltonian ``` -## Lattice -```@docs -super_square_lattice -pegasus_lattice -zephyr_lattice -``` - ## Belief propagation ```@docs local_energy interaction_energy get_neighbors -belief_propagation MergedEnergy update_message -clustered_hamiltonian_2site merge_vertices_cl_h projector SparseCSC @@ -68,7 +57,6 @@ brute_force ## Truncate ```@docs truncate_clustered_hamiltonian_1site_BP -truncate_clustered_hamiltonian_2site_BP truncate_clustered_hamiltonian_2site_energy select_numstate_best ``` diff --git a/docs/src/bp.md b/docs/src/bp.md new file mode 100644 index 0000000..918f826 --- /dev/null +++ b/docs/src/bp.md @@ -0,0 +1,9 @@ +## Belief propagation + +Local dimensional reduction can be achieved by selectively choosing states in the clustered Hamiltonian that have the lowest local energy in the cluster. This approach aims to reduce the dimensionality of the problem by focusing on the most relevant and energetically favorable states. It can be done by truncation based on energy or truncation based on Loopy Belief Propagation. + +```@docs +clustered_hamiltonian_2site +belief_propagation +truncate_clustered_hamiltonian_2site_BP +``` \ No newline at end of file diff --git a/docs/src/clh.md b/docs/src/clh.md new file mode 100644 index 0000000..894df6d --- /dev/null +++ b/docs/src/clh.md @@ -0,0 +1,25 @@ +# Introduction +A clustered Hamiltonian is a graphical representation that allows for a convenient and intuitive way to describe the structure of a network. + +The concept of a clustered Hamiltonian within `SpinGlassNetworks.jl` introduces a powerful mechanism for organizing spins into desired geometries, facilitating a structured approach to modeling complex spin systems. Analogous to a factor graph, the clustered Hamiltonian involves nodes that represent tensors within the underlying network. The edges connecting these nodes in the clustered Hamiltonian correspond to the indices shared between the respective tensors in the tensor network. + +```@docs +clustered_hamiltonian +``` + +## Simple example + +```@example +using SpinGlassNetworks + +# Prepare simple instance +instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, +(1, 2) => -1.0, (2, 3) => 1.0) +ig = ising_graph(instance) + +# Create clustered Hamiltonian. +cl_h = clustered_hamiltonian( + ig, + cluster_assignment_rule = super_square_lattice((3, 1, 1)) +) +``` \ No newline at end of file diff --git a/docs/src/ising.md b/docs/src/ising.md new file mode 100644 index 0000000..eb81764 --- /dev/null +++ b/docs/src/ising.md @@ -0,0 +1,25 @@ +# Introduction + +The Ising model is a mathematical model used to describe the behavior of interacting particles, such as atoms or molecules, in a magnetic field. In the Ising model, each particle is represented as a binary variable $s_i$ that can take on the values of either +1 or -1. The total energy of the system is given by the Hamiltonian: + +$$H = \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$$ + +where $J_{ij}$ is the coupling constant between particles $i$ and $j$, $h_i$ is the external magnetic field at particle $i$, and the sum is taken over all pairs of particles and all particles in the system $\mathcal{E}$, respectively. + +```@docs +ising_graph +``` + +## Simple example +```@example +using SpinGlassNetworks +# Create Ising instance +instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, +(1, 2) => -1.0, (2, 3) => 1.0) + +# Generate Ising graph +ig = ising_graph(instance) + +# View graph properties +@show biases(ig), couplings(ig) +``` \ No newline at end of file diff --git a/docs/src/lattice.md b/docs/src/lattice.md new file mode 100644 index 0000000..ac7698f --- /dev/null +++ b/docs/src/lattice.md @@ -0,0 +1,90 @@ +## Lattice +Within the `SpinGlassNetworks.jl` package, users have the flexibility to construct various lattice geometries, each tailored to specific needs. With these diverse lattice geometries, SpinGlassNetworks empowers users to model and study complex spin systems with a high degree of flexibility and precision. + +## Super square lattice +The `super_square_lattice` geometry represents a square lattice where unit cells consist of multiple spins, offering the unique feature of accommodating diagonal next-nearest-neighbor interactions. This geometry allows for a nuanced exploration of spin interactions beyond the traditional square lattice framework. + +```@docs +super_square_lattice +``` + +```@example +using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs + +# load Chimera instance and create Ising graph +instance = "$(@__DIR__)/../../src/instances/square_diagonal/5x5/diagonal.txt" +ig = ising_graph(instance) + +# Loaded instance is zephyr graph +m = 5 +n = 5 +t = 4 + +cl_h = clustered_hamiltonian( + ig, + cluster_assignment_rule = super_square_lattice((m, n, t)) +) + +println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))) +``` + +## Pegasus graphs +The Pegasus graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. It is designed to provide a grid of qubits with specific connectivity patterns optimized for solving certain optimization problems. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#pegasus-graph). +```@raw html + +``` + +```@docs +pegasus_lattice +``` + +```@example +using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs + +# load Chimera instance and create Ising graph +instance = "$(@__DIR__)/../../src/instances/pegasus_random/P4/RAU/001_sg.txt" +ig = ising_graph(instance) + +# Loaded instance is pegasus graph +m = 3 +n = 3 +t = 3 + +cl_h = clustered_hamiltonian( + ig, + cluster_assignment_rule = pegasus_lattice((m, n, t)) +) + +println("Number of nodes in original instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))) +``` + + +## Zephyr graphs +The Zephyr graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#zephyr-graph). +```@raw html + +``` + +```@docs +zephyr_lattice +``` + +```@example +using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs + +# load Chimera instance and create Ising graph +instance = "$(@__DIR__)/../../src/instances/zephyr_random/Z3/RAU/001_sg.txt" +ig = ising_graph(instance) + +# Loaded instance is zephyr graph +m = 6 +n = 6 +t = 4 + +cl_h = clustered_hamiltonian( + ig, + cluster_assignment_rule = zephyr_lattice((m, n, t)) +) + +println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))) +``` \ No newline at end of file diff --git a/docs/src/userguide.md b/docs/src/userguide.md index acdd7f6..ebfd29f 100644 --- a/docs/src/userguide.md +++ b/docs/src/userguide.md @@ -1,125 +1,5 @@ # Introduction -This section provides examples of how to use the 'ising_graph' function to generate an Ising model graph and the 'clustered_hamiltonian' function to convert the Ising graph into a clustered Hamiltonian. -# Ising Graph -The Ising model is a mathematical model used to describe the behavior of interacting particles, such as atoms or molecules, in a magnetic field. In the Ising model, each particle is represented as a binary variable $s_i$ that can take on the values of either +1 or -1. The total energy of the system is given by the Hamiltonian: +A [Julia](http://julialang.org) package for building and interacting with Ising spin glass models in context of tensor networks. Part of [SpinGlassPEPS](https://github.com/euro-hpc-pl/SpinGlassPEPS.jl) package. -$$H = \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$$ - -where $J_{ij}$ is the coupling constant between particles $i$ and $j$, $h_i$ is the external magnetic field at particle $i$, and the sum is taken over all pairs of particles and all particles in the system $\mathcal{E}$, respectively. - - -## Simple example -```@example -using SpinGlassNetworks -# Create Ising instance -instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, -(1, 2) => -1.0, (2, 3) => 1.0) - -# Generate Ising graph -ig = ising_graph(instance) - -# View graph properties -@show biases(ig), couplings(ig) -``` - -## Generalisation - -The 'ising_graph' function is quite general function. One can easly convert instance into another hamiltonian convention, ex. -```math -H = - \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j - \mu \sum_{i} h_i s_i -``` - -'ising_graph' also allows for building other spin system, not only spin-``\frac{1}{2}`` system. For example one may build chain where sites allows for 3 spin values. - -```@example -using SpinGlassNetworks - -# Create spin chain instance -instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, -(1, 2) => -1.0, (2, 3) => 1.0) - -rank_override = Dict(1 => 3, 2 => 3, 3 => 3) - -sg = ising_graph(instance, rank_override=rank_override) - -# see ranks of each site -rank_vec(sg) -``` - -# Clustered Hamiltonian - -A clustered Hamiltonian is a graphical representation that allows for a convenient and intuitive way to describe the structure of a tensor network. - -A clustered Hamiltonian consists of two types of nodes: variable nodes and factor nodes. Variable nodes represent the tensors in the tensor network, and factor nodes represent the operations that are applied to those tensors. - -Each variable node in the clustered Hamiltonian corresponds to a tensor in the tensor network, and each factor node corresponds to a tensor contraction or operation that is applied to one or more of those tensors. The edges between the nodes in the clustered Hamiltonian represent the indices that are shared between the corresponding tensors in the tensor network. - -## Simple example - -```@example -using SpinGlassNetworks - -# Prepare simple instance -instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, -(1, 2) => -1.0, (2, 3) => 1.0) -ig = ising_graph(instance) - -# Create clustered Hamiltonian. -cl_h = clustered_hamiltonian( - ig, - cluster_assignment_rule = super_square_lattice((3, 1, 1)) -) -``` - -## Pegasus graphs -The Pegasus graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. It is designed to provide a grid of qubits with specific connectivity patterns optimized for solving certain optimization problems. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#pegasus-graph). -```@raw html - -``` - -```@example -using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs - -# load Chimera instance and create Ising graph -instance = "$(@__DIR__)/../../src/instances/pegasus_random/P4/RAU/001_sg.txt" -ig = ising_graph(instance) - -# Loaded instance is pegasus graph -m = 3 -n = 3 -t = 3 - -cl_h = clustered_hamiltonian( - ig, - cluster_assignment_rule = pegasus_lattice((m, n, t)) -) - -println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))) -``` - - -## Zephyr graphs -The Zephyr graph is a type of graph architecture used in quantum computing systems, particularly in the quantum annealing machines developed by D-Wave Systems. Futer details can be found [here](https://docs.dwavesys.com/docs/latest/c_gs_4.html#zephyr-graph). -```@raw html - -``` -```@example -using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs - -# load Chimera instance and create Ising graph -instance = "$(@__DIR__)/../../src/instances/zephyr_random/Z3/RAU/001_sg.txt" -ig = ising_graph(instance) - -# Loaded instance is zephyr graph -m = 6 -n = 6 -t = 4 - -cl_h = clustered_hamiltonian( - ig, - cluster_assignment_rule = zephyr_lattice((m, n, t)) -) - -println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))) -``` \ No newline at end of file +The contents of our package are richly illustrated through comprehensive examples, showcasing the practical utilization of key functions. Specifically, the 'ising_graph' function is highlighted, demonstrating its capacity to generate Ising model graphs—a fundamental step in modeling spin systems. Additionally, the 'clustered_hamiltonian' function is presented as a pivotal tool for converting Ising graphs into clustered Hamiltonians. The package delves into various lattice geometries, providing insights into constructing diverse structures such as the super_square_lattice, pegasus lattice, and zephyr lattice. Moreover, the documentation outlines methods for local dimensional reduction, shedding light on techniques to streamline computations and enhance the efficiency of spin system simulations. From caded78173e8d9c98796910ae9d111ec866728ae Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Fri, 17 Nov 2023 14:59:14 +0100 Subject: [PATCH 186/218] rmf clustered hamiltonian v1.0 --- examples/temp.jl | 36 +++++++++++++++++------------------ src/clustered_hamiltonian.jl | 37 ++++++++++++++++++++++++++++++++++++ 2 files changed, 55 insertions(+), 18 deletions(-) diff --git a/examples/temp.jl b/examples/temp.jl index 689cada..acab58d 100644 --- a/examples/temp.jl +++ b/examples/temp.jl @@ -1,5 +1,6 @@ using HDF5 using LightGraphs +using LinearAlgebra using LabelledGraphs using MetaGraphs using SpinGlassNetworks @@ -74,36 +75,34 @@ function load_openGM(fname::String, Nx::Integer, Ny::Integer) result end -function energy_rmf() - -end - function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 320) loaded_rmf = load_openGM(fname, Nx, Ny) functions = loaded_rmf["fun"] factors = loaded_rmf["fac"] N = loaded_rmf["N"] - println(size(N)) - node_factors = Dict() - edge_factors = Dict() - for index in keys(factors) - if length(index) == 4 - push!(edge_factors, index=>factors[index]) - else - push!(node_factors, index=>factors[index]) - end - end - println(length(node_factors)) - println((0,0) in collect(keys(node_factors))) - g = grid((Nx,Ny)) clusters = super_square_lattice((Nx, Ny, 1)) cl_h = LabelledGraph{MetaDiGraph}(sort(collect(values(clusters)))) for v ∈ cl_h.labels x, y = v - sp = Spectrum([node_factors[(y-1, x-1)]], Array([collect(1:N[y, x])]), Vector{Int}([])) + sp = Spectrum(Vector{Real}(undef, 1), Array{Vector{Int}}(undef, 1, 1), Vector{Int}(undef, 1)) set_props!(cl_h, v, Dict(:cluster => v, :spectrum => sp)) end + for (index, value) in factors + if length(index) == 2 + y, x = index + Eng = sum(functions[value]) + set_props!(cl_h, (x+1, y+1), Dict(:eng => Eng)) + elseif length(index) == 4 + y1, x1, y2, x2 = index + add_edge!(cl_h, (x1 + 1, y1 + 1), (x2 + 1, y2 + 1)) + Eng = sum(functions[value], dims=2) + set_props!(cl_h, (x1 + 1, y1 + 1), (x2 + 1, y2 + 1), Dict(:outer_edges=> ((x1 + 1, y1 + 1), (x2 + 1, y2 + 1)), + :eng => Eng, :pl => I, :pr => I)) + else + throw(ErrorException("Something is wrong with factor index, it has length $(length(index))")) + end + end cl_h end @@ -114,3 +113,4 @@ filename = "/home/tsmierzchalski/.julia/dev/SpinGlassNetworks/examples/penguin-s cf = clustered_hamiltonian(filename, x, y) + diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index b7c6d27..b4fefe4 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -463,3 +463,40 @@ function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) new_cl_h end + +function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 320) + loaded_rmf = load_openGM(fname, Nx, Ny) + functions = loaded_rmf["fun"] + factors = loaded_rmf["fac"] + N = loaded_rmf["N"] + + clusters = super_square_lattice((Nx, Ny, 1)) + cl_h = LabelledGraph{MetaDiGraph}(sort(collect(values(clusters)))) + lp = PoolOfProjectors{Int}() + for v ∈ cl_h.labels + x, y = v + sp = Spectrum(Vector{Real}(undef, 1), Array{Vector{Int}}(undef, 1, 1), Vector{Int}(undef, 1)) + set_props!(cl_h, v, Dict(:cluster => v, :spectrum => sp)) + end + for (index, value) in factors + if length(index) == 2 + y, x = index + Eng = sum(functions[value]) + set_props!(cl_h, (x+1, y+1), Dict(:en => Eng)) + elseif length(index) == 4 + y1, x1, y2, x2 = index + add_edge!(cl_h, (x1 + 1, y1 + 1), (x2 + 1, y2 + 1)) + Eng = sum(functions[value], dims=2) + n = length(Eng) + ipl = add_projector!(lp, ones(n)) + ipr = add_projector!(lp, ones(n)) + set_props!(cl_h, (x1 + 1, y1 + 1), (x2 + 1, y2 + 1), Dict(:outer_edges=> ((x1 + 1, y1 + 1), (x2 + 1, y2 + 1)), + :en => Eng, :ipl => ipl, :ipr => ipr)) + else + throw(ErrorException("Something is wrong with factor index, it has length $(length(index))")) + end + end + + set_props!(cl_h, Dict(:pool_of_projectors => lp)) + cl_h +end \ No newline at end of file From 2c37b7bf6cc217af020bac79be7fa5d16c0cd8ba Mon Sep 17 00:00:00 2001 From: annamariadziubyna <73058800+annamariadziubyna@users.noreply.github.com> Date: Sun, 19 Nov 2023 18:19:39 +0100 Subject: [PATCH 187/218] add the docs --- docs/make.jl | 2 +- docs/src/clh.md | 15 ++++++++++++--- docs/src/ising.md | 14 +++++++++----- docs/src/lattice.md | 27 +++++++++++++++++++++------ src/ising.jl | 9 ++++----- src/lattice.jl | 11 ++++++----- 6 files changed, 53 insertions(+), 25 deletions(-) diff --git a/docs/make.jl b/docs/make.jl index c54d524..21f5b06 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -2,8 +2,8 @@ using Documenter, SpinGlassNetworks _pages = [ "User guide" => "userguide.md", - "Lattice geometries" => "lattice.md", "Ising graph" => "ising.md", + "Lattice geometries" => "lattice.md", "Clustered hamiltonian" => "clh.md", "Local dimensional reduction" => "bp.md", "API Reference for auxiliary functions" => "api.md" diff --git a/docs/src/clh.md b/docs/src/clh.md index 894df6d..fde9b6c 100644 --- a/docs/src/clh.md +++ b/docs/src/clh.md @@ -3,6 +3,16 @@ A clustered Hamiltonian is a graphical representation that allows for a convenie The concept of a clustered Hamiltonian within `SpinGlassNetworks.jl` introduces a powerful mechanism for organizing spins into desired geometries, facilitating a structured approach to modeling complex spin systems. Analogous to a factor graph, the clustered Hamiltonian involves nodes that represent tensors within the underlying network. The edges connecting these nodes in the clustered Hamiltonian correspond to the indices shared between the respective tensors in the tensor network. +The Ising problem in translates to: +$$ H(\conf{x}{\Nbar}) = \sum_{\langle m,n\rangle \in \mathcal{F}} E_{x_m x_n} + \sum_{n=1}^{\Nbar} E_{x_n} $$ +$\mathcal{F}$ forms a 2D graph, see the figure below, where we indicate nearest-neighbour interactions with blue lines, and diagonal connections with green lines. +Each $x_n$ takes $d$ values with $d=2^4$ for square diagonal, $d=2^{24}$ for Pegasus and $2^{16}$ for Zephyr geometry. +$E_{x_n}$ is an intra--node energy of the corresponding binary-variables configuration, and $E_{x_n x_m}$ is inter--node energy. + +```@raw html + +``` + ```@docs clustered_hamiltonian ``` @@ -13,13 +23,12 @@ clustered_hamiltonian using SpinGlassNetworks # Prepare simple instance -instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, -(1, 2) => -1.0, (2, 3) => 1.0) +instance = "$(@__DIR__)/../../src/instances/square_diagonal/5x5/diagonal.txt" ig = ising_graph(instance) # Create clustered Hamiltonian. cl_h = clustered_hamiltonian( ig, - cluster_assignment_rule = super_square_lattice((3, 1, 1)) + cluster_assignment_rule = super_square_lattice((5,5,4)) ) ``` \ No newline at end of file diff --git a/docs/src/ising.md b/docs/src/ising.md index eb81764..05e066f 100644 --- a/docs/src/ising.md +++ b/docs/src/ising.md @@ -1,4 +1,4 @@ -# Introduction +# Ising model The Ising model is a mathematical model used to describe the behavior of interacting particles, such as atoms or molecules, in a magnetic field. In the Ising model, each particle is represented as a binary variable $s_i$ that can take on the values of either +1 or -1. The total energy of the system is given by the Hamiltonian: @@ -6,20 +6,24 @@ $$H = \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$$ where $J_{ij}$ is the coupling constant between particles $i$ and $j$, $h_i$ is the external magnetic field at particle $i$, and the sum is taken over all pairs of particles and all particles in the system $\mathcal{E}$, respectively. +In `SpinGlassPEPS.jl` package, an ising graph can be created using the command `ising_graph`. ```@docs ising_graph ``` ## Simple example +In this simple example below we show how to create ising_graph of a instance given as txt file in a format (i, j, Jij). The resulting graph has vertices (black circles) corresponding to positions of spins in the system and edges defining coupling strength between spins. Each vertex contains information about local field. + ```@example using SpinGlassNetworks # Create Ising instance -instance = Dict((1, 1) => 1.0, (2, 2) => 0.5, (3, 3) => -0.25, -(1, 2) => -1.0, (2, 3) => 1.0) - -# Generate Ising graph +instance = "$(@__DIR__)/../../src/instances/square_diagonal/5x5/diagonal.txt" ig = ising_graph(instance) # View graph properties @show biases(ig), couplings(ig) +``` + +```@raw html + ``` \ No newline at end of file diff --git a/docs/src/lattice.md b/docs/src/lattice.md index ac7698f..a2a44d4 100644 --- a/docs/src/lattice.md +++ b/docs/src/lattice.md @@ -1,21 +1,28 @@ -## Lattice +## Lattice geometries +The Ising graph allowed for loading instances directly from a file and translating it into a graph. The next step towards constructing the tensor network is to build a lattice, based on which we will transform the Ising graph into a clustered Hamiltonian. Within the `SpinGlassNetworks.jl` package, users have the flexibility to construct various lattice geometries, each tailored to specific needs. With these diverse lattice geometries, SpinGlassNetworks empowers users to model and study complex spin systems with a high degree of flexibility and precision. ## Super square lattice -The `super_square_lattice` geometry represents a square lattice where unit cells consist of multiple spins, offering the unique feature of accommodating diagonal next-nearest-neighbor interactions. This geometry allows for a nuanced exploration of spin interactions beyond the traditional square lattice framework. +The `super_square_lattice` geometry represents a square lattice with nearest neighbors interactions (horizontal and vertical interactions between unit cells) and next nearest neighbor interactions (diagonal interactions). Unit cells depicted on the schematic picture below as red ellipses can consist of multiple spins. +This geometry allows for a nuanced exploration of spin interactions beyond the traditional square lattice framework. +```@raw html + +``` + +In `SpinGlassPEPS.jl` solver, a grid of this type can be loaded using the command `super_square_lattice`. ```@docs super_square_lattice ``` +Below you find simple example of usage `super_square_latttice` function. + ```@example using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs -# load Chimera instance and create Ising graph instance = "$(@__DIR__)/../../src/instances/square_diagonal/5x5/diagonal.txt" ig = ising_graph(instance) -# Loaded instance is zephyr graph m = 5 n = 5 t = 4 @@ -34,10 +41,14 @@ The Pegasus graph is a type of graph architecture used in quantum computing syst ``` +In `SpinGlassPEPS.jl` solver, a grid of this type can be loaded using the command `pegasus_lattice`. + ```@docs pegasus_lattice ``` +Below you find simple example of usage `pegasus_latttice` function. + ```@example using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs @@ -55,7 +66,7 @@ cl_h = clustered_hamiltonian( cluster_assignment_rule = pegasus_lattice((m, n, t)) ) -println("Number of nodes in original instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))) +println("Number of nodes in original instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))/2) ``` @@ -65,10 +76,14 @@ The Zephyr graph is a type of graph architecture used in quantum computing syste ``` +In `SpinGlassPEPS.jl` solver, a grid of this type can be loaded using the command `zephyr_lattice`. + ```@docs zephyr_lattice ``` +Below you find simple example of usage `zephyr_latttice` function. + ```@example using SpinGlassEngine, SpinGlassNetworks, LabelledGraphs @@ -86,5 +101,5 @@ cl_h = clustered_hamiltonian( cluster_assignment_rule = zephyr_lattice((m, n, t)) ) -println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig)), "\n", " Number of nodes in clustered Hamiltonian: ", length(LabelledGraphs.vertices(cl_h))) +println("Number of nodes in oryginal instance: ", length(LabelledGraphs.vertices(ig))) ``` \ No newline at end of file diff --git a/src/ising.jl b/src/ising.jl index 50f0b6a..04e2207 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -25,18 +25,17 @@ $(TYPEDSIGNATURES) Create an Ising graph from interaction data. -This function creates an Ising graph from interaction data provided in the form of an `inst` argument. +This function creates an Ising graph (LabelledGraph) from interaction data provided in the form of an `inst` argument. The Ising graph represents a system of spins, where each spin is associated with a vertex, and interactions between spins are represented as edges with corresponding weights. # Arguments: - `::Type{T}`: The type of the edge weights, typically `Float64` or `Float32`. -- `inst::Instance`: Interaction data, which can be either a file path to a CSV file or a collection of triples `(i, j, J)` -representing interactions between spins, where `i` and `j` are spin indices, and `J` is the interaction strength. -- `scale::Real`: A scaling factor applied to interaction strengths (default is 1). +- `inst::Instance`: Interaction data, which can be either a file path to a CSV file or a collection of triples `(i, j, J)` representing interactions between spins, where `i` and `j` are spin indices, and `J` is the interaction strength. +- `scale::Real`: The scale factor establishes the convention in the Hamiltonian (default is 1). - `rank_override::Dict`: A dictionary specifying the rank (number of states) for each vertex. If not provided, a default rank of 2 is used for all vertices. # Returns: -- `ig::IsingGraph{T}`: The Ising graph representing the spin system. +- `ig::IsingGraph{T}`: The Ising graph (LabelledGraph) representing the spin system. The function reads interaction data and constructs an Ising graph `ig`. It assigns interaction strengths to edges between spins and optionally scales them by the `scale` factor. diff --git a/src/lattice.jl b/src/lattice.jl index 298e160..971e5c6 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -16,7 +16,8 @@ Create a mapping from clustered Hamiltonian coordinates to a super square lattic Variable number of Ising graph -> Factor graph coordinate system This function generates a mapping that relates clustered Hamiltonian coordinates to a super square lattice arrangement. -The super square lattice is defined by the size of five dimensions: `(m, um, n, un, t)`. +The super square lattice is defined by the size of five dimensions: `(m, um, n, un, t)`, +where m is the number of columns, m is the number of rows and t denotes the number of spins stored in the cluster. # Arguments: - `size::NTuple{5, Int}`: A tuple specifying the size of the super square lattice in five dimensions: `(m, um, n, un, t)`. @@ -39,10 +40,10 @@ $(TYPEDSIGNATURES) Create a mapping from clustered Hamiltonian coordinates to a simplified super square lattice arrangement. This function generates a mapping that relates clustered Hamiltonian coordinates to a simplified super square lattice arrangement. -The simplified super square lattice is defined by the size of three dimensions: `(m, n, t)`. +The simplified super square lattice is defined by the size of three dimensions: `(m, n, t)`, where m is the number of columns, n is the number of rows and t denotes the number of spins stored in the cluster. # Arguments: -- `size::NTuple{3, Int}`: A tuple specifying the size of the simplified super square lattice in three dimensions: `(m, n, t)`. +- `size::NTuple{3, Int}`: A tuple specifying the size of the simplified super square lattice in three dimensions: `(m, n, t)`, where `m` is number of columns, `n` number of rows and `t` denotes numberr of spins in cluster. # Returns: - `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding lattice coordinates. @@ -66,7 +67,7 @@ This function generates a mapping that relates clustered Hamiltonian coordinates based on the specified size of the Pegasus lattice in three dimensions: `(m, n, t)`. # Arguments: -- `size::NTuple{3, Int}`: A tuple specifying the size of the Pegasus lattice in three dimensions: `(m, n, t)`. +- `size::NTuple{3, Int}`: A tuple specifying the size of the Pegasus lattice in three dimensions: `(m, n, t)`, where `m` is number of columns, `n` number of rows and `t` denotes numberr of spins in cluster. Convention: `t` is already divided by 8, so `t`=3 for Pegasus lattice. # Returns: - `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding Pegasus lattice coordinates. @@ -142,7 +143,7 @@ This function generates a mapping that relates clustered Hamiltonian coordinates coordinates based on the specified size of the Zephyr lattice in three dimensions: `(m, n, t)`. # Arguments: -- `size::NTuple{3, Int}`: A tuple specifying the size of the Zephyr lattice in three dimensions: `(m, n, t)`. +- `size::NTuple{3, Int}`: A tuple specifying the size of the Zephyr lattice in three dimensions: `(m, n, t)`, where `m` is double number of columns, `n` double number of rows and `t` denotes number of spins in cluster. Convention: `t` is already divided by 4, so `t`=4 for Zephyr lattice. # Returns: - `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding Zephyr lattice coordinates. From 7290d9694448d2bb810d9c263b191265ccc521f6 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Tue, 21 Nov 2023 11:57:20 +0100 Subject: [PATCH 188/218] bugfix --- src/clustered_hamiltonian.jl | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index b4fefe4..756a0f1 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -474,22 +474,20 @@ function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 3 cl_h = LabelledGraph{MetaDiGraph}(sort(collect(values(clusters)))) lp = PoolOfProjectors{Int}() for v ∈ cl_h.labels - x, y = v - sp = Spectrum(Vector{Real}(undef, 1), Array{Vector{Int}}(undef, 1, 1), Vector{Int}(undef, 1)) - set_props!(cl_h, v, Dict(:cluster => v, :spectrum => sp)) + set_props!(cl_h, v, Dict(:cluster => v)) end for (index, value) in factors if length(index) == 2 y, x = index Eng = sum(functions[value]) - set_props!(cl_h, (x+1, y+1), Dict(:en => Eng)) + sp = Spectrum([Eng], [collect(1:8), collect(1:8)], zeros(1)) + set_props!(cl_h, (x+1, y+1), Dict(:spectrum => sp)) elseif length(index) == 4 y1, x1, y2, x2 = index add_edge!(cl_h, (x1 + 1, y1 + 1), (x2 + 1, y2 + 1)) - Eng = sum(functions[value], dims=2) - n = length(Eng) - ipl = add_projector!(lp, ones(n)) - ipr = add_projector!(lp, ones(n)) + Eng = sum(functions[value], dims=1) + ipl = add_projector!(lp, collect(1:N[y1+1, x1+1])) + ipr = add_projector!(lp, collect(1:N[y2+1, x2+1])) set_props!(cl_h, (x1 + 1, y1 + 1), (x2 + 1, y2 + 1), Dict(:outer_edges=> ((x1 + 1, y1 + 1), (x2 + 1, y2 + 1)), :en => Eng, :ipl => ipl, :ipr => ipr)) else @@ -498,5 +496,6 @@ function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 3 end set_props!(cl_h, Dict(:pool_of_projectors => lp)) + println(lp) cl_h end \ No newline at end of file From f54b9266ab9493b9137cf5dbfb5094eaee8ba17f Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Tue, 21 Nov 2023 13:19:13 +0100 Subject: [PATCH 189/218] fix the bug in RMF clustered hamiltonian --- src/clustered_hamiltonian.jl | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index 756a0f1..b711a35 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -479,13 +479,13 @@ function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 3 for (index, value) in factors if length(index) == 2 y, x = index - Eng = sum(functions[value]) - sp = Spectrum([Eng], [collect(1:8), collect(1:8)], zeros(1)) + Eng = functions[value]' + sp = Spectrum(collect(Eng), [collect(1:8), collect(1:8)], zeros(1)) set_props!(cl_h, (x+1, y+1), Dict(:spectrum => sp)) elseif length(index) == 4 y1, x1, y2, x2 = index add_edge!(cl_h, (x1 + 1, y1 + 1), (x2 + 1, y2 + 1)) - Eng = sum(functions[value], dims=1) + Eng = functions[value] ipl = add_projector!(lp, collect(1:N[y1+1, x1+1])) ipr = add_projector!(lp, collect(1:N[y2+1, x2+1])) set_props!(cl_h, (x1 + 1, y1 + 1), (x2 + 1, y2 + 1), Dict(:outer_edges=> ((x1 + 1, y1 + 1), (x2 + 1, y2 + 1)), @@ -496,6 +496,5 @@ function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 3 end set_props!(cl_h, Dict(:pool_of_projectors => lp)) - println(lp) cl_h end \ No newline at end of file From 653ccd9b3934f3b58a27e5bcd16e2fd1f9b5b99f Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Tue, 21 Nov 2023 14:48:27 +0100 Subject: [PATCH 190/218] clean up cluster hamiltonian for RMF --- src/clustered_hamiltonian.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index b711a35..2ca6486 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -480,7 +480,7 @@ function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 3 if length(index) == 2 y, x = index Eng = functions[value]' - sp = Spectrum(collect(Eng), [collect(1:8), collect(1:8)], zeros(1)) + sp = Spectrum(collect(Eng), Vector{Vector{Int}}[], zeros(1)) set_props!(cl_h, (x+1, y+1), Dict(:spectrum => sp)) elseif length(index) == 4 y1, x1, y2, x2 = index From 5987b75d2a0e528728d798d6f855de1f7a9398d3 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 22 Nov 2023 12:46:23 +0100 Subject: [PATCH 191/218] change cl_h spectrum --- src/clustered_hamiltonian.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index 2ca6486..4b8f8a2 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -480,7 +480,7 @@ function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 3 if length(index) == 2 y, x = index Eng = functions[value]' - sp = Spectrum(collect(Eng), Vector{Vector{Int}}[], zeros(1)) + sp = Spectrum(collect(Eng), Vector{Vector{Int}}[], zeros(Int, N[y+1, x+1])) set_props!(cl_h, (x+1, y+1), Dict(:spectrum => sp)) elseif length(index) == 4 y1, x1, y2, x2 = index From 2ab5ce12fe2f57a094f7883c6d5350c7b6408002 Mon Sep 17 00:00:00 2001 From: tomsmierz Date: Wed, 22 Nov 2023 14:36:45 +0100 Subject: [PATCH 192/218] added sizes for benchmark instances and allowed diagonal conections --- src/clustered_hamiltonian.jl | 11 ++++++++--- src/utils.jl | 25 +++++++++++++++++++++---- 2 files changed, 29 insertions(+), 7 deletions(-) diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index 4b8f8a2..eeead8c 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -464,13 +464,18 @@ function truncate_clustered_hamiltonian(cl_h::LabelledGraph{S, T}, states::Dict) new_cl_h end -function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 320) +function clustered_hamiltonian(fname::String, + Nx::Union{Integer, Nothing}=nothing, + Ny::Union{Integer, Nothing}=nothing) + loaded_rmf = load_openGM(fname, Nx, Ny) functions = loaded_rmf["fun"] factors = loaded_rmf["fac"] N = loaded_rmf["N"] - clusters = super_square_lattice((Nx, Ny, 1)) + X, Y = loaded_rmf["Nx"], loaded_rmf["Ny"] + + clusters = super_square_lattice((X, Y, 1)) cl_h = LabelledGraph{MetaDiGraph}(sort(collect(values(clusters)))) lp = PoolOfProjectors{Int}() for v ∈ cl_h.labels @@ -495,6 +500,6 @@ function clustered_hamiltonian(fname::String, Nx::Integer = 240, Ny::Integer = 3 end end - set_props!(cl_h, Dict(:pool_of_projectors => lp)) + set_props!(cl_h, Dict(:pool_of_projectors => lp, :Nx => X, :Ny => Y)) cl_h end \ No newline at end of file diff --git a/src/utils.jl b/src/utils.jl index d043242..83b4d1d 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -104,7 +104,7 @@ Args: Returns: dictionary with factors and funcitons defining the energy functional. """ -function load_openGM(fname::String, Nx::Integer, Ny::Integer) +function load_openGM(fname::String, Nx::Union{Integer, Nothing}=nothing, Ny::Union{Integer, Nothing}=nothing) file = h5open(fname, "r") file_keys = collect(keys(read(file))) @@ -115,6 +115,11 @@ function load_openGM(fname::String, Nx::Integer, Ny::Integer) V = Array{Real}(data["function-id-16000"]["values"]) N = Array{Int64}(data["numbers-of-states"]) + if isnothing(Nx) || isnothing(Ny) + filename, _ = splitext(basename(fname)) + Nx, Ny = benchmark_names[filename] + end + F = reverse(F) factors = Dict() @@ -131,8 +136,8 @@ function load_openGM(fname::String, Nx::Integer, Ny::Integer) end if length(n) == 4 - if abs(n[1] - n[3]) + abs(n[2] - n[4]) != 1 - throw(ErrorException("Not nearest neighbour")) + if abs(n[1] - n[3]) + abs(n[2] - n[4]) ∉ [1,2] || (abs(n[1] - n[3]) + abs(n[2] - n[4]) == 2 && (abs(n[1] - n[3]) == 2 || abs(n[2] - n[4]))) + throw(ErrorException("Not nearest neighbour or diagonal neighbors")) end end @@ -171,4 +176,16 @@ function load_openGM(fname::String, Nx::Integer, Ny::Integer) result = Dict("fun" => functions, "fac" => factors, "N" => reshape(N, (Ny, Nx)), "Nx" => Nx, "Ny" => Ny) result -end \ No newline at end of file +end + +benchmark_names = Dict( + "penguin-small" => (240,320), + "palm-small" => (240,360), + "clownfish-small" => (240,360), + "crops-small" => (240,360), + "pfau-small" => (240,320), + "lake-small" => (240,360), + "snail" => (240,320), + "fourcolors" => (240,320), + "strawberry-glass-2-small" => (320,240) +) \ No newline at end of file From a1aaf232288dd98755b801e6094b690c9324e6a2 Mon Sep 17 00:00:00 2001 From: annamariadziubyna Date: Wed, 22 Nov 2023 16:28:25 +0100 Subject: [PATCH 193/218] fix the bug in reading h5 instances --- src/utils.jl | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/utils.jl b/src/utils.jl index 83b4d1d..fc49ffd 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -134,9 +134,8 @@ function load_openGM(fname::String, Nx::Union{Integer, Nothing}=nothing, Ny::Uni ny, nx = divrem(tt, Nx) push!(n, ny, nx) end - if length(n) == 4 - if abs(n[1] - n[3]) + abs(n[2] - n[4]) ∉ [1,2] || (abs(n[1] - n[3]) + abs(n[2] - n[4]) == 2 && (abs(n[1] - n[3]) == 2 || abs(n[2] - n[4]))) + if abs(n[1] - n[3]) + abs(n[2] - n[4]) ∉ [1,2] || (abs(n[1] - n[3]) + abs(n[2] - n[4]) == 2 && (abs(n[1] - n[3]) == 2 || abs(n[2] - n[4] == 2))) throw(ErrorException("Not nearest neighbour or diagonal neighbors")) end end From 0eb5aac7195ce86401c0f11c23d4361019a7cc08 Mon Sep 17 00:00:00 2001 From: annamariadziubyna <73058800+annamariadziubyna@users.noreply.github.com> Date: Thu, 23 Nov 2023 19:27:24 +0100 Subject: [PATCH 194/218] add docs --- docs/src/api.md | 3 +-- docs/src/clh.md | 12 +----------- docs/src/ising.md | 10 +++------- docs/src/userguide.md | 2 +- 4 files changed, 6 insertions(+), 21 deletions(-) diff --git a/docs/src/api.md b/docs/src/api.md index 342a2fe..cf987b7 100644 --- a/docs/src/api.md +++ b/docs/src/api.md @@ -1,7 +1,5 @@ # Library ---- - ```@meta CurrentModule = SpinGlassNetworks ``` @@ -64,4 +62,5 @@ select_numstate_best ## Auxiliary Functions ```@docs zephyr_to_linear +load_openGM ``` \ No newline at end of file diff --git a/docs/src/clh.md b/docs/src/clh.md index fde9b6c..6f11909 100644 --- a/docs/src/clh.md +++ b/docs/src/clh.md @@ -3,16 +3,6 @@ A clustered Hamiltonian is a graphical representation that allows for a convenie The concept of a clustered Hamiltonian within `SpinGlassNetworks.jl` introduces a powerful mechanism for organizing spins into desired geometries, facilitating a structured approach to modeling complex spin systems. Analogous to a factor graph, the clustered Hamiltonian involves nodes that represent tensors within the underlying network. The edges connecting these nodes in the clustered Hamiltonian correspond to the indices shared between the respective tensors in the tensor network. -The Ising problem in translates to: -$$ H(\conf{x}{\Nbar}) = \sum_{\langle m,n\rangle \in \mathcal{F}} E_{x_m x_n} + \sum_{n=1}^{\Nbar} E_{x_n} $$ -$\mathcal{F}$ forms a 2D graph, see the figure below, where we indicate nearest-neighbour interactions with blue lines, and diagonal connections with green lines. -Each $x_n$ takes $d$ values with $d=2^4$ for square diagonal, $d=2^{24}$ for Pegasus and $2^{16}$ for Zephyr geometry. -$E_{x_n}$ is an intra--node energy of the corresponding binary-variables configuration, and $E_{x_n x_m}$ is inter--node energy. - -```@raw html - -``` - ```@docs clustered_hamiltonian ``` @@ -26,7 +16,7 @@ using SpinGlassNetworks instance = "$(@__DIR__)/../../src/instances/square_diagonal/5x5/diagonal.txt" ig = ising_graph(instance) -# Create clustered Hamiltonian. +# Create clustered Hamiltonian cl_h = clustered_hamiltonian( ig, cluster_assignment_rule = super_square_lattice((5,5,4)) diff --git a/docs/src/ising.md b/docs/src/ising.md index 05e066f..2d24bb9 100644 --- a/docs/src/ising.md +++ b/docs/src/ising.md @@ -2,17 +2,17 @@ The Ising model is a mathematical model used to describe the behavior of interacting particles, such as atoms or molecules, in a magnetic field. In the Ising model, each particle is represented as a binary variable $s_i$ that can take on the values of either +1 or -1. The total energy of the system is given by the Hamiltonian: -$$H = \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$$ +$H = \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$ where $J_{ij}$ is the coupling constant between particles $i$ and $j$, $h_i$ is the external magnetic field at particle $i$, and the sum is taken over all pairs of particles and all particles in the system $\mathcal{E}$, respectively. -In `SpinGlassPEPS.jl` package, an ising graph can be created using the command `ising_graph`. +In `SpinGlassPEPS.jl` package, an Ising graph can be created using the command `ising_graph`. ```@docs ising_graph ``` ## Simple example -In this simple example below we show how to create ising_graph of a instance given as txt file in a format (i, j, Jij). The resulting graph has vertices (black circles) corresponding to positions of spins in the system and edges defining coupling strength between spins. Each vertex contains information about local field. +In this simple example below we show how to create Ising graph of a instance given as txt file in a format (i, j, Jij). The resulting graph has vertices (black circles) corresponding to positions of spins in the system and edges defining coupling strength between spins. Each vertex contains information about local field. ```@example using SpinGlassNetworks @@ -22,8 +22,4 @@ ig = ising_graph(instance) # View graph properties @show biases(ig), couplings(ig) -``` - -```@raw html - ``` \ No newline at end of file diff --git a/docs/src/userguide.md b/docs/src/userguide.md index ebfd29f..c3d7b52 100644 --- a/docs/src/userguide.md +++ b/docs/src/userguide.md @@ -2,4 +2,4 @@ A [Julia](http://julialang.org) package for building and interacting with Ising spin glass models in context of tensor networks. Part of [SpinGlassPEPS](https://github.com/euro-hpc-pl/SpinGlassPEPS.jl) package. -The contents of our package are richly illustrated through comprehensive examples, showcasing the practical utilization of key functions. Specifically, the 'ising_graph' function is highlighted, demonstrating its capacity to generate Ising model graphs—a fundamental step in modeling spin systems. Additionally, the 'clustered_hamiltonian' function is presented as a pivotal tool for converting Ising graphs into clustered Hamiltonians. The package delves into various lattice geometries, providing insights into constructing diverse structures such as the super_square_lattice, pegasus lattice, and zephyr lattice. Moreover, the documentation outlines methods for local dimensional reduction, shedding light on techniques to streamline computations and enhance the efficiency of spin system simulations. +The contents of our package are richly illustrated through comprehensive examples, showcasing the practical utilization of key functions. Specifically, the `ising_graph` function is highlighted, demonstrating its capacity to generate Ising model graphs—a fundamental step in modeling spin systems. Additionally, the `clustered_hamiltonian` function is presented as a pivotal tool for converting Ising graphs into clustered Hamiltonians. The package delves into various lattice geometries, providing insights into constructing diverse structures such as the `super_square_lattice`, `pegasus_lattice`, and `zephyr-lattice`. Moreover, the documentation outlines methods for local dimensional reduction, shedding light on techniques to streamline computations and enhance the efficiency of spin system simulations. From d7311b4f7ac56200ad3064d576903d68a9ae1c65 Mon Sep 17 00:00:00 2001 From: annamariadziubyna <73058800+annamariadziubyna@users.noreply.github.com> Date: Mon, 27 Nov 2023 13:07:04 +0100 Subject: [PATCH 195/218] add the docs --- docs/src/clh.md | 2 +- docs/src/ising.md | 2 +- docs/src/lattice.md | 8 +++---- docs/src/userguide.md | 2 +- src/bp.jl | 25 ++++++++++----------- src/clustered_hamiltonian.jl | 33 ++++++++++++--------------- src/ising.jl | 5 +++-- src/lattice.jl | 43 ++++++++++++++++++------------------ src/truncate.jl | 2 +- 9 files changed, 58 insertions(+), 64 deletions(-) diff --git a/docs/src/clh.md b/docs/src/clh.md index 6f11909..c3ba34a 100644 --- a/docs/src/clh.md +++ b/docs/src/clh.md @@ -1,7 +1,7 @@ # Introduction A clustered Hamiltonian is a graphical representation that allows for a convenient and intuitive way to describe the structure of a network. -The concept of a clustered Hamiltonian within `SpinGlassNetworks.jl` introduces a powerful mechanism for organizing spins into desired geometries, facilitating a structured approach to modeling complex spin systems. Analogous to a factor graph, the clustered Hamiltonian involves nodes that represent tensors within the underlying network. The edges connecting these nodes in the clustered Hamiltonian correspond to the indices shared between the respective tensors in the tensor network. +The concept of a clustered Hamiltonian within `SpinGlassNetworks.jl` introduces a mechanism for organizing spins into desired geometries, facilitating a structured approach to modeling complex spin systems. Analogous to a standard factor graph, the clustered Hamiltonian involves nodes that represent tensors within the underlying network. The edges connecting these nodes in the clustered Hamiltonian correspond to the indices shared between the respective tensors in the tensor network. ```@docs clustered_hamiltonian diff --git a/docs/src/ising.md b/docs/src/ising.md index 2d24bb9..f2bec58 100644 --- a/docs/src/ising.md +++ b/docs/src/ising.md @@ -12,7 +12,7 @@ ising_graph ``` ## Simple example -In this simple example below we show how to create Ising graph of a instance given as txt file in a format (i, j, Jij). The resulting graph has vertices (black circles) corresponding to positions of spins in the system and edges defining coupling strength between spins. Each vertex contains information about local field. +In this simple example below we show how to create Ising graph of a instance given as txt file in a format (i, j, Jij). The resulting graph has vertices corresponding to positions of spins in the system and edges defining coupling strength between spins. Each vertex contains information about local field. ```@example using SpinGlassNetworks diff --git a/docs/src/lattice.md b/docs/src/lattice.md index a2a44d4..773462e 100644 --- a/docs/src/lattice.md +++ b/docs/src/lattice.md @@ -1,10 +1,10 @@ -## Lattice geometries -The Ising graph allowed for loading instances directly from a file and translating it into a graph. The next step towards constructing the tensor network is to build a lattice, based on which we will transform the Ising graph into a clustered Hamiltonian. -Within the `SpinGlassNetworks.jl` package, users have the flexibility to construct various lattice geometries, each tailored to specific needs. With these diverse lattice geometries, SpinGlassNetworks empowers users to model and study complex spin systems with a high degree of flexibility and precision. +# Lattice geometries +The Ising graph allowed for loading instances directly from a file and translating them into a graph. The next step towards constructing the tensor network is to build a lattice, based on which we will transform the Ising graph into a clustered Hamiltonian. +Within the `SpinGlassNetworks.jl` package, users have the flexibility to construct three types of lattice geometries, each tailored to specific needs. ## Super square lattice The `super_square_lattice` geometry represents a square lattice with nearest neighbors interactions (horizontal and vertical interactions between unit cells) and next nearest neighbor interactions (diagonal interactions). Unit cells depicted on the schematic picture below as red ellipses can consist of multiple spins. -This geometry allows for a nuanced exploration of spin interactions beyond the traditional square lattice framework. +This geometry allows for an exploration of spin interactions beyond the traditional square lattice framework. ```@raw html ``` diff --git a/docs/src/userguide.md b/docs/src/userguide.md index c3d7b52..cb92310 100644 --- a/docs/src/userguide.md +++ b/docs/src/userguide.md @@ -2,4 +2,4 @@ A [Julia](http://julialang.org) package for building and interacting with Ising spin glass models in context of tensor networks. Part of [SpinGlassPEPS](https://github.com/euro-hpc-pl/SpinGlassPEPS.jl) package. -The contents of our package are richly illustrated through comprehensive examples, showcasing the practical utilization of key functions. Specifically, the `ising_graph` function is highlighted, demonstrating its capacity to generate Ising model graphs—a fundamental step in modeling spin systems. Additionally, the `clustered_hamiltonian` function is presented as a pivotal tool for converting Ising graphs into clustered Hamiltonians. The package delves into various lattice geometries, providing insights into constructing diverse structures such as the `super_square_lattice`, `pegasus_lattice`, and `zephyr-lattice`. Moreover, the documentation outlines methods for local dimensional reduction, shedding light on techniques to streamline computations and enhance the efficiency of spin system simulations. +The contents of our package are illustrated through comprehensive examples, showcasing the practical utilization of key functions. Specifically, the `ising_graph` function is highlighted, demonstrating its capacity to generate Ising model graphs — a fundamental step in modeling spin systems. Additionally, the `clustered_hamiltonian` function is presented as a tool for converting Ising graphs into clustered Hamiltonians. The package delves into various lattice geometries, providing insights into constructing diverse structures such as the `super_square_lattice`, `pegasus_lattice`, and `zephyr_lattice`. Moreover, the documentation outlines methods for local dimensional reduction, shedding light on techniques to streamline computations and enhance the efficiency of spin system simulations. diff --git a/src/bp.jl b/src/bp.jl index bc8286f..92ab0f4 100644 --- a/src/bp.jl +++ b/src/bp.jl @@ -13,23 +13,22 @@ export """ $(TYPEDSIGNATURES) -Perform belief propagation on a given clustered hamiltonian. +Perform loopy belief propagation on a given clustered Hamiltonian. # Arguments: -- `cl_h::LabelledGraph{S, T}`: The clustered hamiltonian represented as a labeled graph. -- `beta::Real`: The temperature parameter for the belief propagation algorithm. -- `tol::Real (optional, default=1e-6)`: The convergence tolerance. -The algorithm stops when the message updates between iterations are smaller than this value. +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labelled graph. +- `beta::Real`: The inverse temperature parameter for the belief propagation algorithm. +- `tol::Real (optional, default=1e-6)`: The convergence tolerance. The algorithm stops when the message updates between iterations are smaller than this value. - `iter::Int (optional, default=1)`: The maximum number of iterations to perform. # Returns: - `beliefs::Dict`: A dictionary where keys are vertices of clustered hamiltonian, and values are the resulting beliefs after belief propagation. -The function implements belief propagation on the given clustered hamiltonian `cl_h` to calculate beliefs for each vertex. +The function implements loopy belief propagation on the given clustered hamiltonian `cl_h` to calculate beliefs for each vertex. Belief propagation is an iterative algorithm that computes beliefs by passing messages between vertices and edges of the clustered hamiltonian. The algorithm continues until convergence or until the specified maximum number of iterations is reached. -The beliefs are computed based on the temperature parameter `beta`, which controls the influence of energy values on the beliefs. +The beliefs are computed based on the inverse temperature parameter `beta`, which controls the influence of energy values on the beliefs. """ function belief_propagation(cl_h::LabelledGraph{S, T}, beta::Real; tol=1e-6, iter=1) where {S, T} messages_ve = Dict() @@ -247,17 +246,17 @@ end """ $(TYPEDSIGNATURES) -Constructs a clustered Hamiltonian for a given clustered Hamiltonian with a 2-site cluster approximation. +Constructs a clustered Hamiltonian for a given clustered Hamiltonian with a 2-site cluster approximation used in Pegasus graph. # Arguments: -- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. -- `beta::Real`: The temperature parameter for the 2-site cluster Hamiltonian construction. +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labelled graph. +- `beta::Real`: The inverse temperature parameter for the 2-site cluster Hamiltonian construction. # Returns: -- `new_cl_h::LabelledGraph{MetaDiGraph}`: A new labeled graph representing the 2-site cluster Hamiltonian. +- `new_cl_h::LabelledGraph{MetaDiGraph}`: A new labelled graph representing the 2-site cluster Hamiltonian. - This function constructs a clustered Hamiltonian `cl_h` by applying a 2-site cluster approximation. - It combines and merges vertices and edges of the original graph to create a simplified representation of the Hamiltonian. +This function constructs a clustered Hamiltonian `cl_h` by applying a 2-site cluster approximation. +It combines and merges vertices and edges of the original graph to create a simplified representation of the Hamiltonian. The resulting `new_cl_h` graph represents the 2-site cluster Hamiltonian with simplified interactions between clusters. The energy values, projectors, and spectra associated with the new vertices and edges are computed based on diff --git a/src/clustered_hamiltonian.jl b/src/clustered_hamiltonian.jl index eeead8c..d1a3a89 100644 --- a/src/clustered_hamiltonian.jl +++ b/src/clustered_hamiltonian.jl @@ -46,19 +46,17 @@ This function constructs a clustered Hamiltonian from an Ising graph by introduc # Arguments: - `ig::IsingGraph`: The Ising graph representing the spin system. -- `num_states_cl::Int`: The number of states per cluster. -- `spectrum::Function`: A function for calculating the spectrum of the clustered Hamiltonian. -- `cluster_assignment_rule::Dict{Int, L}`: A dictionary specifying the assignment rule that maps Ising graph vertices to clusters. +- `num_states_cl::Int`: The number of states per cluster taken into account when calculating the spectrum. In every cluster the number of states is constant. +- `spectrum::Function`: A function for calculating the spectrum of the clustered Hamiltonian. It can be `full_spectrum` or `brute_force`. +- `cluster_assignment_rule::Dict{Int, L}`: A dictionary specifying the assignment rule that maps Ising graph vertices to clusters. It can be `super_square_lattice`, `pegasus_lattice` or `zephyr_lattice`. # Returns: -- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labelled graph. The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by introducing a natural order in clustered Hamiltonian coordinates. It allows you to specify the number of states per cluster, a spectrum calculation function, and a cluster assignment rule, which maps Ising graph vertices to clusters. - -This function is useful for organizing and studying spin systems in a clustered Hamiltonian framework. """ function clustered_hamiltonian( ig::IsingGraph, @@ -79,18 +77,17 @@ This function constructs a clustered Hamiltonian from an Ising graph by introduc # Arguments: - `ig::IsingGraph`: The Ising graph representing the spin system. -- `num_states_cl::Dict{T, Int}`: A dictionary specifying the number of states per cluster for different clusters. -- `spectrum::Function`: A function for calculating the spectrum of the clustered Hamiltonian. -- `cluster_assignment_rule::Dict{Int, T}`: A dictionary specifying the assignment rule that maps Ising graph vertices to clusters. +- `num_states_cl::Dict{T, Int}`: A dictionary specifying the number of states per cluster for different clusters. Number of states are considered when calculating the spectrum. +- `spectrum::Function`: A function for calculating the spectrum of the clustered Hamiltonian. It can be `full_spectrum` or `brute_force`. +- `cluster_assignment_rule::Dict{Int, T}`: A dictionary specifying the assignment rule that maps Ising graph vertices to clusters. It can be `super_square_lattice`, `pegasus_lattice` or `zephyr_lattice`. # Returns: -- `cl_h::LabelledGraph{MetaDiGraph}`: The clustered Hamiltonian represented as a labeled graph. +- `cl_h::LabelledGraph{MetaDiGraph}`: The clustered Hamiltonian represented as a labelled graph. The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by introducing a natural order in clustered Hamiltonian coordinates. It allows you to specify the number of -states per cluster, a spectrum calculation function, and a cluster assignment rule, which maps Ising graph vertices to clusters. - -This function is useful for organizing and studying spin systems in a clustered Hamiltonian framework. +states per cluster which can vary for different clusters, a spectrum calculation function, +and a cluster assignment rule, which maps Ising graph vertices to clusters. """ function clustered_hamiltonian( @@ -149,20 +146,18 @@ This function constructs a clustered Hamiltonian from an Ising graph by introduc # Arguments: - `ig::IsingGraph`: The Ising graph representing the spin system. -- `spectrum::Function`: A function for calculating the spectrum of the clustered Hamiltonian. -- `cluster_assignment_rule::Dict{Int, T}`: A dictionary specifying the assignment rule that maps Ising graph vertices to clusters. +- `spectrum::Function`: A function for calculating the spectrum of the clustered Hamiltonian. It can be `full_spectrum` or `brute_force`. Default is `full_spectrum`. +- `cluster_assignment_rule::Dict{Int, T}`: A dictionary specifying the assignment rule that maps Ising graph vertices to clusters. It can be `super_square_lattice`, `pegasus_lattice` or `zephyr_lattice`. # Returns: -- `cl_h::LabelledGraph{MetaDiGraph}`: The clustered Hamiltonian represented as a labeled graph. +- `cl_h::LabelledGraph{MetaDiGraph}`: The clustered Hamiltonian represented as a labelled graph. The `clustered_hamiltonian` function takes an Ising graph (`ig`) as input and constructs a clustered Hamiltonian by introducing a natural order in clustered Hamiltonian coordinates. You can optionally specify a spectrum calculation function and a cluster assignment rule, which maps Ising graph vertices to clusters. - +This version of `clustered_hamiltonian` function does not truncate states in the cluster while calculating the spectrum. If you want to specify custom cluster sizes, use the alternative version of this function by passing a `Dict{T, Int}` containing the number of states per cluster as `num_states_cl`. - -This function is useful for organizing and studying spin systems in a clustered Hamiltonian framework. """ function clustered_hamiltonian( ig::IsingGraph; diff --git a/src/ising.jl b/src/ising.jl index 04e2207..4229ec3 100644 --- a/src/ising.jl +++ b/src/ising.jl @@ -26,7 +26,8 @@ $(TYPEDSIGNATURES) Create an Ising graph from interaction data. This function creates an Ising graph (LabelledGraph) from interaction data provided in the form of an `inst` argument. -The Ising graph represents a system of spins, where each spin is associated with a vertex, and interactions between spins are represented as edges with corresponding weights. +The Ising graph represents a system of spins, where each spin is associated with a vertex, +and interactions between spins are represented as edges with corresponding weights. # Arguments: - `::Type{T}`: The type of the edge weights, typically `Float64` or `Float32`. @@ -38,7 +39,7 @@ The Ising graph represents a system of spins, where each spin is associated with - `ig::IsingGraph{T}`: The Ising graph (LabelledGraph) representing the spin system. The function reads interaction data and constructs an Ising graph `ig`. -It assigns interaction strengths to edges between spins and optionally scales them by the `scale` factor. +It assigns interaction strengths to edges between spins and optionally scales them by the `scale` factor. 'Scale' option allows for the change of convention in the Hamiltonian. The `rank_override` dictionary can be used to specify the rank (number of states) for individual vertices, allowing customization of the Ising model. Convention: H = scale * sum_{i, j} (J_{ij} * s_i * s_j + J_{ii} * s_i) """ diff --git a/src/lattice.jl b/src/lattice.jl index 971e5c6..5ef94c4 100644 --- a/src/lattice.jl +++ b/src/lattice.jl @@ -12,21 +12,21 @@ export """ $(TYPEDSIGNATURES) -Create a mapping from clustered Hamiltonian coordinates to a super square lattice arrangement. -Variable number of Ising graph -> Factor graph coordinate system +Create a mapping from Ising graph coordinates to a super square lattice arrangement. +Variable number of Ising graph -> cluster hamiltonian coordinate system -This function generates a mapping that relates clustered Hamiltonian coordinates to a super square lattice arrangement. +This function generates a mapping that relates Ising graph coordinates to a super square lattice arrangement. The super square lattice is defined by the size of five dimensions: `(m, um, n, un, t)`, -where m is the number of columns, m is the number of rows and t denotes the number of spins stored in the cluster. +where m is the number of columns, n is the number of rows and t denotes the number of spins stored in the cluster. # Arguments: - `size::NTuple{5, Int}`: A tuple specifying the size of the super square lattice in five dimensions: `(m, um, n, un, t)`. # Returns: -- `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding lattice coordinates. +- `coord_map::Dict`: A dictionary that maps Ising graph coordinates to the corresponding lattice coordinates. The `size` tuple represents the dimensions of the super square lattice. The function creates a dictionary where -clustered Hamiltonian coordinates are associated with their corresponding lattice coordinates. +ising graph coordinates are associated with their corresponding lattice coordinates. """ function super_square_lattice(size::NTuple{5, Int}) m, um, n, un, t = size @@ -37,16 +37,17 @@ end """ $(TYPEDSIGNATURES) -Create a mapping from clustered Hamiltonian coordinates to a simplified super square lattice arrangement. +Create a mapping from Ising graph coordinates to a simplified super square lattice arrangement. -This function generates a mapping that relates clustered Hamiltonian coordinates to a simplified super square lattice arrangement. -The simplified super square lattice is defined by the size of three dimensions: `(m, n, t)`, where m is the number of columns, n is the number of rows and t denotes the number of spins stored in the cluster. +This function generates a mapping that relates Ising graph coordinates to a simplified super square lattice arrangement. +The simplified super square lattice is defined by the size of three dimensions: `(m, n, t)`, where m is the number of columns, +n is the number of rows and t denotes the number of spins stored in the cluster. # Arguments: - `size::NTuple{3, Int}`: A tuple specifying the size of the simplified super square lattice in three dimensions: `(m, n, t)`, where `m` is number of columns, `n` number of rows and `t` denotes numberr of spins in cluster. # Returns: -- `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding lattice coordinates. +- `coord_map::Dict`: A dictionary that maps Ising graph coordinates to the corresponding lattice coordinates. The `size` tuple represents the dimensions of the simplified super square lattice. The function internally adds the required dimensions `(1, 1)` to make it compatible with the `super_square_lattice` function, which deals with five dimensions. @@ -61,19 +62,18 @@ pegasus_lattice(size::NTuple{2, Int}) = pegasus_lattice((size[1], size[2], 3)) """ $(TYPEDSIGNATURES) -Create a mapping from clustered Hamiltonian coordinates to Pegasus lattice coordinates. +Create a mapping from Ising graph coordinates to Pegasus lattice coordinates. -This function generates a mapping that relates clustered Hamiltonian coordinates to Pegasus lattice coordinates +This function generates a mapping that relates Ising graph coordinates to Pegasus lattice coordinates based on the specified size of the Pegasus lattice in three dimensions: `(m, n, t)`. # Arguments: -- `size::NTuple{3, Int}`: A tuple specifying the size of the Pegasus lattice in three dimensions: `(m, n, t)`, where `m` is number of columns, `n` number of rows and `t` denotes numberr of spins in cluster. Convention: `t` is already divided by 8, so `t`=3 for Pegasus lattice. +- `size::NTuple{3, Int}`: A tuple specifying the size of the Pegasus lattice in three dimensions: `(m, n, t)`, where `m` is number of columns, `n` number of rows and `t` denotes number of spins in cluster. Convention: `t` is already divided by 8, so `t`=3 for Pegasus lattice. # Returns: -- `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding Pegasus lattice coordinates. +- `coord_map::Dict`: A dictionary that maps Ising graph coordinates to the corresponding Pegasus lattice coordinates. -The Pegasus lattice is a specialized lattice used in quantum computing, and this function allows you to convert -between clustered Hamiltonian coordinates and Pegasus lattice coordinates. +The `pegasus_lattice` allows you to build the graph relevant for D-Wave Pegasus architecture. """ function pegasus_lattice(size::NTuple{3, Int}) m, n, t = size @@ -137,19 +137,18 @@ zephyr_lattice(size::NTuple{2, Int}) = zephyr_lattice((size[1], size[2], 4)) """ $(TYPEDSIGNATURES) -Create a mapping from clustered Hamiltonian coordinates to Zephyr lattice coordinates. +Create a mapping from Ising graph coordinates to Zephyr lattice coordinates. -This function generates a mapping that relates clustered Hamiltonian coordinates to Zephyr lattice +This function generates a mapping that relates Ising graph coordinates to Zephyr lattice coordinates based on the specified size of the Zephyr lattice in three dimensions: `(m, n, t)`. # Arguments: -- `size::NTuple{3, Int}`: A tuple specifying the size of the Zephyr lattice in three dimensions: `(m, n, t)`, where `m` is double number of columns, `n` double number of rows and `t` denotes number of spins in cluster. Convention: `t` is already divided by 4, so `t`=4 for Zephyr lattice. +- `size::NTuple{3, Int}`: A tuple specifying the size of the Zephyr lattice in three dimensions: `(m, n, t)`, where `m` is double number of columns, `n` double number of rows and `t` denotes number of spins in cluster. Convention: `t` is already divided by 4, so `t`=4 for Zephyr lattice. E.g. to create 3x3x16 Zephyr lattice, you should use `m`=6, `n`=6, `t`=4. # Returns: -- `coord_map::Dict`: A dictionary that maps clustered Hamiltonian coordinates to the corresponding Zephyr lattice coordinates. +- `coord_map::Dict`: A dictionary that maps Ising graph coordinates to the corresponding Zephyr lattice coordinates. -The Zephyr lattice is a specialized lattice used in quantum computing, and this function allows you to -convert between clustered Hamiltonian coordinates and Zephyr lattice coordinates. +The `zephyr_lattice` allows you to build the graph relevant for D-Wave Zephyr architecture. """ function zephyr_lattice(size::NTuple{3, Int}) m, n, t = size diff --git a/src/truncate.jl b/src/truncate.jl index 1ae5f63..b434200 100644 --- a/src/truncate.jl +++ b/src/truncate.jl @@ -80,7 +80,7 @@ This function truncates a clustered Hamiltonian by considering 2-site belief pro to keep. It computes the beliefs for all 2-site combinations and selects the states that maximize the probability. # Arguments: -- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labeled graph. +- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labelled graph. - `beliefs::Dict`: A dictionary containing belief values for 2-site interactions. - `num_states::Int`: The maximum number of most probable states to keep. - `beta::Real (optional)`: The inverse temperature parameter (default is 1.0). From dc802115fed5e5a8dca784a5b3142555b1bd813f Mon Sep 17 00:00:00 2001 From: annamariadziubyna <73058800+annamariadziubyna@users.noreply.github.com> Date: Tue, 19 Dec 2023 16:27:02 +0100 Subject: [PATCH 196/218] add png images --- docs/src/images/annealing.png | Bin 0 -> 158010 bytes docs/src/images/bb.png | Bin 0 -> 251134 bytes docs/src/images/branch_bound.png | Bin 0 -> 205318 bytes docs/src/images/clustering.png | Bin 0 -> 218294 bytes docs/src/images/contract.png | Bin 0 -> 177418 bytes docs/src/images/explain.png | Bin 0 -> 126496 bytes docs/src/images/graphs.png | Bin 0 -> 588457 bytes docs/src/images/lattice.png | Bin 0 -> 494009 bytes docs/src/images/layout.png | Bin 0 -> 224396 bytes docs/src/images/peg.png | Bin 0 -> 1510774 bytes docs/src/images/pegasus.png | Bin 0 -> 1161525 bytes docs/src/images/peps_graph.png | Bin 0 -> 610483 bytes docs/src/images/prob.png | Bin 0 -> 238668 bytes docs/src/images/sd.png | Bin 0 -> 1546916 bytes docs/src/images/square_cross_double.png | 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