mirror of
https://github.com/kalmarek/PropertyT.jl.git
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156 lines
4.5 KiB
Julia
156 lines
4.5 KiB
Julia
using JuMP
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import Base: rationalize
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using GroupAlgebras
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function products{T}(U::AbstractVector{T}, V::AbstractVector{T})
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result = Vector{T}()
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for u in U
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for v in V
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push!(result, u*v)
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end
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end
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return unique(result)
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end
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function create_product_matrix(basis, limit)
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product_matrix = zeros(Int, (limit,limit))
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for i in 1:limit
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x_inv::eltype(basis) = inv(basis[i])
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for j in 1:limit
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w = x_inv*basis[j]
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index = findfirst(basis, w)
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index ≠ 0 || throw(ArgumentError("Product is not supported on basis: $w"))
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product_matrix[i,j] = index
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end
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end
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return product_matrix
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end
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function constraints_from_pm(pm, total_length=maximum(pm))
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n = size(pm,1)
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constraints = constraints = [Array{Int,1}[] for x in 1:total_length]
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for j in 1:n
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Threads.@threads for i in 1:n
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idx = pm[i,j]
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push!(constraints[idx], [i,j])
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end
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end
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return constraints
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end
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function splaplacian_coeff(S, basis, n=length(basis))
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result = spzeros(n)
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result[1] = length(S)
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for s in S
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ind = findfirst(basis, s)
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result[ind] += -1
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end
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return result
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end
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function laplacian_coeff(S, basis)
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return full(splaplacian_coeff(S,basis))
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end
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function create_SDP_problem(matrix_constraints, Δ::GroupAlgebraElement)
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N = size(Δ.product_matrix,1)
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const Δ² = Δ*Δ
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@assert length(Δ) == length(matrix_constraints)
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m = JuMP.Model();
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JuMP.@variable(m, A[1:N, 1:N], SDP)
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JuMP.@SDconstraint(m, A >= zeros(size(A)))
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JuMP.@variable(m, κ >= 0.0)
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JuMP.@objective(m, Max, κ)
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for (pairs, δ², δ) in zip(matrix_constraints, Δ².coefficients, Δ.coefficients)
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JuMP.@constraint(m, sum(A[i,j] for (i,j) in pairs) == δ² - κ*δ)
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end
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return m
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end
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function solve_SDP(sdp_constraints, Δ, solver; verbose=true)
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SDP_problem = create_SDP_problem(sdp_constraints, Δ);
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verbose && @show solver
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JuMP.setsolver(SDP_problem, solver);
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verbose && @show SDP_problem
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# @time MathProgBase.writeproblem(SDP_problem, "/tmp/SDP_problem")
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solution_status = JuMP.solve(SDP_problem);
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verbose && @show solution_status
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if solution_status != :Optimal
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throw(ExceptionError("The solver did not solve the problem successfully!"))
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else
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κ = SDP_problem.objVal;
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A = JuMP.getvalue(JuMP.getvariable(SDP_problem, :A));;
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end
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return κ, A
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end
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function EOI{T<:Number}(Δ::GroupAlgebraElement{T}, κ::T)
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return Δ*Δ - κ*Δ
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end
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function square_as_elt(vector, elt)
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zzz = zeros(elt.coefficients)
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zzz[1:length(vector)] = vector
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# new_base_elt = GroupAlgebraElement(zzz, elt.product_matrix)
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# return (new_base_elt*new_base_elt).coefficients
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return GroupAlgebras.algebra_multiplication(zzz, zzz, elt.product_matrix)
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end
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function compute_SOS{T<:Number}(sqrt_matrix::Array{T,2},
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elt::GroupAlgebraElement{T})
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n = size(sqrt_matrix,2)
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# result = zeros(T, length(elt.coefficients))
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result = @parallel (+) for i in 1:n
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square_as_elt(sqrt_matrix[:,i], elt)
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end
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return GroupAlgebraElement{T}(result, elt.product_matrix)
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end
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function correct_to_augmentation_ideal{T<:Rational}(sqrt_matrix::Array{T,2})
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sqrt_corrected = similar(sqrt_matrix)
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l = size(sqrt_matrix,2)
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for i in 1:l
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col = view(sqrt_matrix,:,i)
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sqrt_corrected[:,i] = col - sum(col)//l
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# @assert sum(sqrt_corrected[:,i]) == 0
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end
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return sqrt_corrected
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end
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function check_solution(κ, sqrt_matrix, Δ; verbose=true, augmented=false)
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result = compute_SOS(sqrt_matrix, Δ)
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if augmented
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@assert GroupAlgebras.ɛ(result) == 0//1
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end
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SOS_diff = EOI(Δ, κ) - result
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eoi_SOS_L₁_dist = norm(SOS_diff,1)
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if verbose
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if augmented
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println("ɛ(Δ² - κΔ - ∑ξᵢ*ξᵢ) = ", GroupAlgebras.ɛ(SOS_diff))
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else
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ɛ_dist = Float64(round(GroupAlgebras.ɛ(SOS_diff),12))
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println("ɛ(Δ² - κΔ - ∑ξᵢ*ξᵢ) ≈ $ɛ_dist")
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end
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L₁_dist = Float64(round(eoi_SOS_L₁_dist, 12))
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println("‖Δ² - κΔ - ∑ξᵢ*ξᵢ‖₁ ≈ $L₁_dist")
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end
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distance_to_cone = 2^3*eoi_SOS_L₁_dist - κ
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return distance_to_cone
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end
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function rationalize{T<:Integer, S<:Real}(::Type{T},
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X::AbstractArray{S}; tol::Real=eps(eltype(X)))
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r(x) = rationalize(T, x, tol=tol)
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return r.(X)
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end;
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ℚ(x, tol::Real) = rationalize(BigInt, x, tol=tol)
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