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add script for SpN_Adj.jl
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scripts/SpN_Adj.jl
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80
scripts/SpN_Adj.jl
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using LinearAlgebra
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BLAS.set_num_threads(8)
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ENV["OMP_NUM_THREADS"] = 1
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using Groups
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import Groups.MatrixGroups
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include(joinpath(@__DIR__, "../test/optimizers.jl"))
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using PropertyT
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using PropertyT.SymbolicWedderburn
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using PropertyT.PermutationGroups
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using PropertyT.StarAlgebras
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include(joinpath(@__DIR__, "argparse.jl"))
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include(joinpath(@__DIR__, "utils.jl"))
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const N = parsed_args["N"]
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const HALFRADIUS = parsed_args["halfradius"]
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const UPPER_BOUND = parsed_args["upper_bound"]
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const GENUS = 2N
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G = MatrixGroups.SymplecticGroup{GENUS}(Int8)
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RG, S, sizes =
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@time PropertyT.group_algebra(G, halfradius=HALFRADIUS, twisted=true)
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wd = let RG = RG, N = N
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G = StarAlgebras.object(RG)
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P = PermGroup(perm"(1,2)", Perm(circshift(1:N, -1)))
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Σ = Groups.Constructions.WreathProduct(PermGroup(perm"(1,2)"), P)
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# Σ = P
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act = PropertyT.action_by_conjugation(G, Σ)
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@info "Computing WedderburnDecomposition"
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wdfl = @time SymbolicWedderburn.WedderburnDecomposition(
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Float64,
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Σ,
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act,
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basis(RG),
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StarAlgebras.Basis{UInt16}(@view basis(RG)[1:sizes[HALFRADIUS]]),
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)
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end
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Δ = RG(length(S)) - sum(RG(s) for s in S)
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Δs = PropertyT.laplacians(
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RG,
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S,
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x -> (gx = PropertyT.grading(x); Set([gx, -gx])),
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)
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# elt = Δ^2
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elt = PropertyT.Adj(Δs, :C₂)
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unit = Δ
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@time model, varP = PropertyT.sos_problem_primal(
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elt,
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unit,
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wd,
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upper_bound=UPPER_BOUND,
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augmented=true,
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show_progress=true
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)
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solve_in_loop(
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model,
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wd,
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varP,
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logdir="./log/r=$HALFRADIUS/Sp($N,Z)/Adj_C₂-InfΔ",
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optimizer=cosmo_optimizer(
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eps=1e-10,
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max_iters=20_000,
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accel=50,
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alpha=1.95,
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),
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data=(elt=elt, unit=unit, halfradius=HALFRADIUS)
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)
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scripts/argparse.jl
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scripts/argparse.jl
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using ArgParse
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args_settings = ArgParseSettings()
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@add_arg_table! args_settings begin
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"-N"
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help = "the degree/genus/etc. parameter for a group"
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arg_type = Int
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default = 3
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"--halfradius", "-R"
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help = "the halfradius on which perform the sum of squares decomposition"
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arg_type = Int
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default = 2
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"--upper_bound", "-u"
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help = "set upper bound for the optimization problem to speed-up the convergence"
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arg_type = Float64
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default = Inf
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end
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parsed_args = parse_args(ARGS, args_settings)
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scripts/utils.jl
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scripts/utils.jl
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using Dates
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using Serialization
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using Logging
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import JuMP
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function get_solution(model)
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λ = JuMP.value(model[:λ])
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Q = real.(sqrt(JuMP.value.(model[:P])))
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solution = Dict(:λ => λ, :Q => Q)
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return solution
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end
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function get_solution(model, wd, varP; logdir)
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λ = JuMP.value(model[:λ])
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Qs = [real.(sqrt(JuMP.value.(P))) for P in varP]
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Q = PropertyT.reconstruct(Qs, wd)
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solution = Dict(:λ => λ, :Q => Q)
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return solution
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end
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function solve_in_loop(model::JuMP.Model, args...; logdir, optimizer, data)
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@info "logging to $logdir"
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status = JuMP.UNKNOWN_RESULT_STATUS
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warm = try
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solution = deserialize(joinpath(logdir, "solution.sjl"))
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warm = solution[:warm]
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@info "trying to warm-start model with λ=$(solution[:λ])..."
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warm
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catch
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nothing
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end
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old_lambda = 0.0
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while status != JuMP.OPTIMAL
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date = now()
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log_file = joinpath(logdir, "solver_$date.log")
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@info "Current logfile is $log_file."
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isdir(dirname(log_file)) || mkpath(dirname(log_file))
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λ, flag, certified_λ = let
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# logstream = current_logger().logger.stream
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# v = @ccall setvbuf(logstream.handle::Ptr{Cvoid}, C_NULL::Ptr{Cvoid}, 1::Cint, 0::Cint)::Cint
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# @warn v
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status, warm = @time PropertyT.solve(log_file, model, optimizer, warm)
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solution = get_solution(model, args...; logdir=logdir)
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solution[:warm] = warm
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serialize(joinpath(logdir, "solution_$date.sjl"), solution)
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serialize(joinpath(logdir, "solution.sjl"), solution)
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flag, λ_cert = open(log_file, append=true) do io
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with_logger(SimpleLogger(io)) do
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PropertyT.certify_solution(
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data.elt,
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data.unit,
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solution[:λ],
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solution[:Q],
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halfradius=data.halfradius,
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)
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end
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end
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solution[:λ], flag, λ_cert
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end
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if flag == true && certified_λ ≥ 0
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@info "Certification done with λ = $certified_λ"
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return certified_λ
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else
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rel_change = abs(certified_λ - old_lambda) / (abs(certified_λ) + abs(old_lambda))
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@info "Certification failed with λ = $λ" certified_λ rel_change
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end
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old_lambda = certified_λ
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if rel_change < 1e-9
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@info "No progress detected, breaking"
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break
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end
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end
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return status == JuMP.OPTIMAL ? old_lambda : NaN
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end
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