using JuMP using SCS export Settings, OrbitData immutable Settings{T<:AbstractMathProgSolver} name::String N::Int G::Group S::Vector autS::Group radius::Int solver::T upper_bound::Float64 tol::Float64 warmstart::Bool end prefix(s::Settings) = s.name suffix(s::Settings) = "$(s.upper_bound)" prepath(s::Settings) = prefix(s) fullpath(s::Settings) = joinpath(prefix(s), suffix(s)) immutable OrbitData{T<:AbstractArray{Float64, 2}, LapType <:AbstractVector{Float64}} name::String Us::Vector{T} Ps::Vector{Array{JuMP.Variable,2}} cnstr::Vector{SparseMatrixCSC{Float64, Int}} laplacian::LapType laplacianSq::LapType dims::Vector{Int} end function OrbitData(sett::Settings) splap = load(filename(prepath(sett), :Δ), "Δ"); pm = load(filename(prepath(sett), :pm), "pm"); cnstr = PropertyT.constraints(pm); splap² = similar(splap) splap² = GroupRings.mul!(splap², splap, splap, pm); Uπs = load(filename(prepath(sett), :Uπs), "Uπs") nzros = [i for i in 1:length(Uπs) if size(Uπs[i],2) !=0] Uπs = Uπs[nzros] Uπs = map(x -> sparsify!(x, sett.tol, verbose=true), Uπs) #dimensions of the corresponding πs: dims = load(filename(prepath(sett), :Uπs), "dims")[nzros] m, P = init_model(size(Uπs,1), [size(U,2) for U in Uπs]); orbits = load(filename(prepath(sett), :orb), "orbits"); n = size(Uπs[1],1) orb_spcnstrm = [orbit_constraint(cnstr[collect(orb)], n) for orb in orbits] orb_splap = orbit_spvector(splap, orbits) orb_splap² = orbit_spvector(splap², orbits) orbData = OrbitData(fullpath(sett), Uπs, P, orb_spcnstrm, orb_splap, orb_splap², dims); # orbData = OrbitData(name, Uπs, P, orb_spcnstrm, splap, splap², dims); return m, orbData end include("OrbitDecomposition.jl") dens(M::SparseMatrixCSC) = nnz(M)/length(M) dens(M::AbstractArray) = countnz(M)/length(M) function sparsify!{Tv,Ti}(M::SparseMatrixCSC{Tv,Ti}, eps=eps(Tv); verbose=false) densM = dens(M) for i in eachindex(M.nzval) if abs(M.nzval[i]) < eps M.nzval[i] = zero(Tv) end end dropzeros!(M) if verbose info("Sparsified density:", rpad(densM, 20), " → ", rpad(dens(M), 20), " ($(nnz(M)) non-zeros)") end return M end function sparsify!{T}(M::AbstractArray{T}, eps=eps(T); verbose=false) densM = dens(M) if verbose info("Sparsifying $(size(M))-matrix... ") end for n in eachindex(M) if abs(M[n]) < eps M[n] = zero(T) end end if verbose info("$(rpad(densM, 20)) → $(rpad(dens(M),20))), ($(countnz(M)) non-zeros)") end return sparse(M) end sparsify{T}(U::AbstractArray{T}, tol=eps(T); verbose=false) = sparsify!(deepcopy(U), tol, verbose=verbose) function transform(U::AbstractArray, V::AbstractArray; sparse=true) if sparse return sparsify!(U'*V*U) else return U'*V*U end end A(data::OrbitData, π, t) = data.dims[π].*transform(data.Us[π], data.cnstr[t]) function constrLHS(m::JuMP.Model, data::OrbitData, t) l = endof(data.Us) lhs = @expression(m, sum(vecdot(A(data, π, t), data.Ps[π]) for π in 1:l)) return lhs end function constrLHS(m::JuMP.Model, cnstr, Us, Ust, dims, vars, eps=100*eps(1.0)) M = [PropertyT.sparsify!(dims[π].*Ust[π]*cnstr*Us[π], eps) for π in 1:endof(Us)] return @expression(m, sum(vecdot(M[π], vars[π]) for π in 1:endof(Us))) end function addconstraints!(m::JuMP.Model, data::OrbitData, l::Int=length(data.laplacian); var::Symbol=:λ) λ = m[var] Ust = [U' for U in data.Us] idx = [π for π in 1:endof(data.Us) if size(data.Us[π],2) != 0] for t in 1:l if t % 100 == 0 print(t, ", ") end # lhs = constrLHS(m, data, t) lhs = constrLHS(m, data.cnstr[t], data.Us[idx], Ust[idx], data.dims[idx], data.Ps[idx]) d, d² = data.laplacian[t], data.laplacianSq[t] # if lhs == zero(lhs) # if d == 0 && d² == 0 # info("Detected empty constraint") # continue # else # warn("Adding unsatisfiable constraint!") # end # end JuMP.@constraint(m, lhs == d² - λ*d) end println("") end function init_model(n, sizes) m = JuMP.Model(); P = Vector{Array{JuMP.Variable,2}}(n) for (k,s) in enumerate(sizes) P[k] = JuMP.@variable(m, [i=1:s, j=1:s]) JuMP.@SDconstraint(m, P[k] >= 0.0) end JuMP.@variable(m, λ >= 0.0) JuMP.@objective(m, Max, λ) return m, P end function create_SDP_problem(sett::Settings) info("Loading orbit data....") @time SDP_problem, orb_data = OrbitData(sett); if sett.upper_bound < Inf λ = JuMP.getvariable(SDP_problem, :λ) JuMP.@constraint(SDP_problem, λ <= sett.upper_bound) end t = length(orb_data.laplacian) info("Adding $t constraints ... ") @time addconstraints!(SDP_problem, orb_data) return SDP_problem, orb_data end function λandP(m::JuMP.Model, data::OrbitData, warmstart=true) varλ = m[:λ] varP = data.Ps λ, Ps = PropertyT.λandP(data.name, m, varλ, varP, warmstart) return λ, Ps end function λandP(m::JuMP.Model, data::OrbitData, sett::Settings) info("Solving SDP problem...") @time λ, Ps = λandP(m, data, sett.warmstart) info("Reconstructing P...") preps = load_preps(filename(prepath(sett), :preps), sett.autS) @time recP = reconstruct_sol(preps, data.Us, Ps, data.dims) fname = filename(fullpath(sett), :P) save(fname, "origP", Ps, "P", recP) return λ, recP end function load_preps(fname::String, G::Group) lded_preps = load(fname, "perms_d") permG = PermutationGroup(length(first(lded_preps))) @assert length(lded_preps) == order(G) return Dict(k=>permG(v) for (k,v) in zip(elements(G), lded_preps)) end function save_preps(fname::String, preps) autS = parent(first(keys(preps))) JLD.save(fname, "perms_d", [preps[elt].d for elt in elements(autS)]) end function check_property_T(sett::Settings) ex(s) = exists(filename(prepath(sett), s)) files_exists = ex.([:pm, :Δ, :Uπs, :orb, :preps]) if !all(files_exists) compute_orbit_data(prepath(sett), sett.S, sett.autS, radius=sett.radius) end cond1 = exists(filename(fullpath(sett), :λ)) cond2 = exists(filename(fullpath(sett), :P)) if !sett.warmstart && cond1 && cond2 λ, P = λandP(fullpath(sett)) else info("Creating SDP problem...") SDP_problem, orb_data = create_SDP_problem(sett) JuMP.setsolver(SDP_problem, sett.solver) info(Base.repr(SDP_problem)) λ, P = λandP(SDP_problem, orb_data, sett) end info("λ = $λ") info("sum(P) = $(sum(P))") info("maximum(P) = $(maximum(P))") info("minimum(P) = $(minimum(P))") isapprox(eigvals(P), abs.(eigvals(P)), atol=sett.tol) || warn("The solution matrix doesn't seem to be positive definite!") return interpret_results(sett.name, sett.S, sett.radius, λ, P) end