using JuMP import Base: rationalize using GroupAlgebras function create_product_matrix(basis, limit) product_matrix = zeros(Int, (limit,limit)) basis_dict = Dict{Array, Int}(x => i for (i,x) in enumerate(basis)) for i in 1:limit x_inv::eltype(basis) = inv(basis[i]) for j in 1:limit w = x_inv*basis[j] product_matrix[i,j] = basis_dict[w] # index = findfirst(basis, w) # index ≠ 0 || throw(ArgumentError("Product is not supported on basis: $w")) # product_matrix[i,j] = index end end return product_matrix end function constraints_from_pm(pm, total_length=maximum(pm)) n = size(pm,1) constraints = constraints = [Array{Int,1}[] for x in 1:total_length] for j in 1:n Threads.@threads for i in 1:n idx = pm[i,j] push!(constraints[idx], [i,j]) end end return constraints end function splaplacian_coeff(S, basis, n=length(basis)) result = spzeros(n) result[1] = float(length(S)) for s in S ind = findfirst(basis, s) result[ind] += -1.0 end return result end function laplacian_coeff(S, basis) return full(splaplacian_coeff(S,basis)) end function create_SDP_problem(matrix_constraints, Δ::GroupAlgebraElement; upper_bound=Inf) N = size(Δ.product_matrix,1) const Δ² = Δ*Δ @assert length(Δ) == length(matrix_constraints) m = JuMP.Model(); JuMP.@variable(m, A[1:N, 1:N], SDP) JuMP.@SDconstraint(m, A >= 0) JuMP.@constraint(m, sum(A[i] for i in eachindex(A)) == 0) JuMP.@variable(m, κ >= 0.0) if upper_bound < Inf JuMP.@constraint(m, κ <= upper_bound) end JuMP.@objective(m, Max, κ) for (pairs, δ², δ) in zip(matrix_constraints, Δ².coefficients, Δ.coefficients) JuMP.@constraint(m, sum(A[i,j] for (i,j) in pairs) == δ² - κ*δ) end return m end function solve_SDP(SDP_problem, solver) @show SDP_problem @show solver JuMP.setsolver(SDP_problem, solver); # @time MathProgBase.writeproblem(SDP_problem, "/tmp/SDP_problem") solution_status = JuMP.solve(SDP_problem); if solution_status != :Optimal warn("The solver did not solve the problem successfully!") end @show solution_status κ = JuMP.getvalue(JuMP.getvariable(SDP_problem, :κ)) A = JuMP.getvalue(JuMP.getvariable(SDP_problem, :A)) return κ, A end function EOI{T<:Number}(Δ::GroupAlgebraElement{T}, κ::T) return Δ*Δ - κ*Δ end @everywhere function square_as_elt(vector, elt) zzz = zeros(elt.coefficients) zzz[1:length(vector)] = vector # new_base_elt = GroupAlgebraElement(zzz, elt.product_matrix) # return (new_base_elt*new_base_elt).coefficients return GroupAlgebras.algebra_multiplication(zzz, zzz, elt.product_matrix) end function compute_SOS{T<:Number}(sqrt_matrix::Array{T,2}, elt::GroupAlgebraElement{T}) n = size(sqrt_matrix,2) # result = zeros(T, length(elt.coefficients)) result = @parallel (+) for i in 1:n square_as_elt(sqrt_matrix[:,i], elt) end return GroupAlgebraElement{T}(result, elt.product_matrix) end function correct_to_augmentation_ideal{T<:Rational}(sqrt_matrix::Array{T,2}) sqrt_corrected = similar(sqrt_matrix) l = size(sqrt_matrix,2) for i in 1:l col = view(sqrt_matrix,:,i) sqrt_corrected[:,i] = col - sum(col)//l # @assert sum(sqrt_corrected[:,i]) == 0 end return sqrt_corrected end function check_solution{T<:Number}(κ::T, sqrt_matrix::Array{T,2}, Δ::GroupAlgebraElement{T}; verbose=true, augmented=false) result = compute_SOS(sqrt_matrix, Δ) if augmented @assert GroupAlgebras.ɛ(result) == 0//1 end SOS_diff = EOI(Δ, κ) - result eoi_SOS_L₁_dist = norm(SOS_diff,1) if verbose @show κ if augmented println("ɛ(Δ² - κΔ - ∑ξᵢ*ξᵢ) = ", GroupAlgebras.ɛ(SOS_diff)) else ɛ_dist = Float64(round(GroupAlgebras.ɛ(SOS_diff),12)) println("ɛ(Δ² - κΔ - ∑ξᵢ*ξᵢ) ≈ $ɛ_dist") end L₁_dist = Float64(round(eoi_SOS_L₁_dist, 12)) println("‖Δ² - κΔ - ∑ξᵢ*ξᵢ‖₁ ≈ $L₁_dist") end distance_to_cone = κ - 2^2*eoi_SOS_L₁_dist return distance_to_cone end function rationalize{T<:Integer, S<:Real}(::Type{T}, X::AbstractArray{S}; tol::Real=eps(eltype(X))) r(x) = rationalize(T, x, tol=tol) return r.(X) end; ℚ(x, tol::Real) = rationalize(BigInt, x, tol=tol) function ℚ_distance_to_positive_cone(Δ::GroupAlgebraElement, κ, A; tol=10.0^-7, verbose=true) isapprox(eigvals(A), abs(eigvals(A)), atol=tol) || warn("The solution matrix doesn't seem to be positive definite!") @assert A == Symmetric(A) A_sqrt = real(sqrtm(A)) println("") println("Checking in floating-point arithmetic...") @time fp_distance = check_solution(κ, A_sqrt, Δ, verbose=verbose) println("Floating point distance (to positive cone) ≈ $(Float64(trunc(fp_distance,8)))") println("-------------------------------------------------------------") println("") if fp_distance ≤ 0 return fp_distance end println("Checking in rational arithmetic...") κ_ℚ = ℚ(trunc(κ,Int(abs(log10(tol)))), tol) A_sqrt_ℚ, Δ_ℚ = ℚ(A_sqrt, tol), ℚ(Δ, tol) @time ℚ_distance = check_solution(κ_ℚ, A_sqrt_ℚ, Δ_ℚ, verbose=verbose) @assert isa(ℚ_distance, Rational) println("Rational distance (to positive cone) ≈ $(Float64(trunc(ℚ_distance,8)))") println("-------------------------------------------------------------") println("") if ℚ_distance ≤ 0 return ℚ_distance end println("Projecting columns of A_sqrt to the augmentation ideal...") A_sqrt_ℚ_aug = correct_to_augmentation_ideal(A_sqrt_ℚ) @time ℚ_dist_to_Σ² = check_solution(κ_ℚ, A_sqrt_ℚ_aug, Δ_ℚ, verbose=verbose, augmented=true) @assert isa(ℚ_dist_to_Σ², Rational) println("Augmentation-projected rational distance (to positive cone)") println("$(Float64(trunc(ℚ_dist_to_Σ²,8))) ≤ κ(G,S)") println("-------------------------------------------------------------") return ℚ_dist_to_Σ² end