using JuMP import MathProgBase: AbstractMathProgSolver 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: $w")) # product_matrix[i,j] = index end end return product_matrix end function constraints_from_pm(pm, total_length) n = size(pm,1) constraints = constraints = [Array{Int,1}[] for x in 1:total_length] for j in 1:n for i in 1:n idx = pm[i,j] push!(constraints[idx], [i,j]) end end return constraints end constraints_from_pm(pm) = constraints_from_pm(pm, maximum(pm)) function splaplacian_coeff(S, basis, n=length(basis)) result = spzeros(n) result[1] = float(length(S)) for s in S ind = findfirst(basis, s) result[ind] += -1.0 end return result end function laplacian_coeff(S, basis) return full(splaplacian_coeff(S,basis)) end function create_SDP_problem(matrix_constraints, Δ::GroupAlgebraElement; upper_bound=Inf) N = size(Δ.product_matrix,1) const Δ² = Δ*Δ @assert length(Δ) == length(matrix_constraints) m = JuMP.Model(); JuMP.@variable(m, A[1:N, 1:N], SDP) JuMP.@SDconstraint(m, A >= 0) JuMP.@constraint(m, sum(A[i] for i in eachindex(A)) == 0) JuMP.@variable(m, κ >= 0.0) if upper_bound < Inf JuMP.@constraint(m, κ <= upper_bound) end JuMP.@objective(m, Max, κ) for (pairs, δ², δ) in zip(matrix_constraints, Δ².coefficients, Δ.coefficients) JuMP.@constraint(m, sum(A[i,j] for (i,j) in pairs) == δ² - κ*δ) end return m end function solve_SDP(SDP_problem, solver) info(logger, Base.repr(SDP_problem)) info(logger, solver) JuMP.setsolver(SDP_problem, solver); # @time MathProgBase.writeproblem(SDP_problem, "/tmp/SDP_problem") solver_logger = basic_config("info") add_handler(solver_logger, DefaultHandler("./$name/solver.log"), "solver") TT = STDOUT redirect_stdout(solver_logger.handlers["solver"].io) solution_status = JuMP.solve(SDP_problem); flush(solver_logger.handlers["solver"].io) remove_handler(solver_logger, "solver") redirect_stdout(TT) if solution_status != :Optimal warn(logger, "The solver did not solve the problem successfully!") end info(logger, solution_status) κ = JuMP.getvalue(JuMP.getvariable(SDP_problem, :κ)) A = JuMP.getvalue(JuMP.getvariable(SDP_problem, :A)) return κ, A end