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PropertyT.jl/src/Orbit-wise.jl

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using JuMP
using SCS
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export Settings, OrbitData
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immutable Settings
name::String
N::Int
G::Group
S::Vector
AutS::Group
radius::Int
solver::SCSSolver
upper_bound::Float64
tol::Float64
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))
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immutable OrbitData
name::String
Us::Vector
Ps::Vector{Array{JuMP.Variable,2}}
cnstr::Vector
laplacian::Vector
laplacianSq::Vector
dims::Vector{Int}
end
function OrbitData(sett::Settings)
splap = load(joinpath(prepath(sett), "delta.jld"), "Δ");
pm = load(joinpath(prepath(sett), "pm.jld"), "pm");
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cnstr = PropertyT.constraints_from_pm(pm);
splap² = similar(splap)
splap² = GroupRings.mul!(splap², splap, splap, pm);
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# Uπs = load(joinpath(name, "U_pis.jld"), "Uπs");
Uπs = load(joinpath(prepath(sett), "U_pis.jld"), "spUπs");
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#dimensions of the corresponding πs:
dims = load(joinpath(prepath(sett), "U_pis.jld"), "dims")
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m, P = init_model(Uπs);
orbits = load(joinpath(prepath(sett), "orbits.jld"), "orbits");
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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);
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# orbData = OrbitData(name, Uπs, P, orb_spcnstrm, splap, splap², dims);
return m, orbData
end
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include("OrbitDecomposition.jl")
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dens(M::SparseMatrixCSC) = length(M.nzval)/length(M)
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dens(M::AbstractArray) = length(findn(M)[1])/length(M)
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function sparsify!{Tv,Ti}(M::SparseMatrixCSC{Tv,Ti}, eps=eps(Tv); verbose=false)
n = nnz(M)
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densM = dens(M)
for i in eachindex(M.nzval)
if abs(M.nzval[i]) < eps
M.nzval[i] = zero(Tv)
end
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end
dropzeros!(M)
m = nnz(M)
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if verbose
info(logger, "Sparsified density:", rpad(densM, 20), "", rpad(dens(M), 20))
end
return M
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end
function sparsify!{T}(M::AbstractArray{T}, eps=eps(T); check=false, verbose=false)
densM = dens(M)
rankM = rank(M)
M[abs.(M) .< eps] .= zero(T)
if check && rankM != rank(M)
warn(logger, "Sparsification decreased the rank!")
end
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if verbose
info(logger, "Sparsified density:", rpad(densM, 20), "", rpad(dens(M),20))
end
return M
end
sparsify{T}(U::AbstractArray{T}, tol=eps(T)) = sparsify!(deepcopy(U), tol)
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function init_orbit_data(logger, sett::Settings; radius=2)
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ex(fname) = isfile(joinpath(prepath(sett), fname))
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files_exists = ex.(["delta.jld", "pm.jld", "U_pis.jld", "orbits.jld"])
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if !all(files_exists)
compute_orbit_data(logger, prepath(sett), sett.G, sett.S, sett.AutS, radius=radius)
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end
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return 0
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end
function transform(U::AbstractArray, V::AbstractArray; sparse=true)
if sparse
return sparsify!(U'*V*U)
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else
return U'*V*U
end
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end
A(data::OrbitData, π, t) = data.dims[π].*transform(data.Us[π], data.cnstr[t])
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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 = 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, = 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 == - λ*d)
end
println("")
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end
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function init_model(Uπs)
m = JuMP.Model();
l = size(Uπs,1)
P = Vector{Array{JuMP.Variable,2}}(l)
for k in 1:l
s = size(Uπs[k],2)
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)
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info(logger, "Loading orbit data....")
t = @timed SDP_problem, orb_data = OrbitData(sett);
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info(logger, PropertyT.timed_msg(t))
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if sett.upper_bound < Inf
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λ = JuMP.getvariable(SDP_problem, )
JuMP.@constraint(SDP_problem, λ <= sett.upper_bound)
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end
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t = length(orb_data.laplacian)
info(logger, "Adding $t constraints ... ")
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t = @timed addconstraints!(SDP_problem, orb_data)
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info(logger, PropertyT.timed_msg(t))
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return SDP_problem, orb_data
end
function λandP(m::JuMP.Model, data::OrbitData)
varλ = m[]
varP = data.Ps
λ, Ps = PropertyT.λandP(data.name, m, varλ, varP)
return λ, Ps
end
function λandP(m::JuMP.Model, data::OrbitData, sett::Settings)
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info(logger, "Solving SDP problem...")
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λ, Ps = λandP(m, data)
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info(logger, "Reconstructing P...")
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t = @timed preps = perm_reps(sett.G, sett.S, sett.AutS, sett.radius)
info(logger, PropertyT.timed_msg(t))
t = @timed recP = reconstruct_sol(preps, data.Us, Ps, data.dims)
info(logger, PropertyT.timed_msg(t))
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fname = PropertyT.λSDPfilenames(fullpath(sett))[2]
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save(fname, "origP", Ps, "P", recP)
return λ, recP
end
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function check_property_T(sett::Settings)
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init_orbit_data(logger, sett, radius=sett.radius)
fnames = PropertyT.λSDPfilenames(fullpath(sett))
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if all(isfile.(fnames))
λ, P = PropertyT.λandP(fullpath(sett))
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else
info(logger, "Creating SDP problem...")
SDP_problem, orb_data = create_SDP_problem(sett)
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JuMP.setsolver(SDP_problem, sett.solver)
λ, P = λandP(SDP_problem, orb_data, sett)
end
info(logger, "λ = ")
info(logger, "sum(P) = $(sum(P))")
info(logger, "maximum(P) = $(maximum(P))")
info(logger, "minimum(P) = $(minimum(P))")
if λ > 0
pm_fname = joinpath(prepath(sett), "pm.jld")
RG = GroupRing(sett.G, load(pm_fname, "pm"))
Δ_fname = joinpath(prepath(sett), "delta.jld")
Δ = GroupRingElem(load(Δ_fname, "Δ")[:, 1], RG)
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isapprox(eigvals(P), abs.(eigvals(P)), atol=sett.tol) ||
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warn("The solution matrix doesn't seem to be positive definite!")
# @assert P == Symmetric(P)
Q = real(sqrtm(Symmetric(P)))
sgap = PropertyT.check_distance_to_positive_cone(Δ, λ, Q, 2*sett.radius, tol=sett.tol, rational=false)
if isa(sgap, Interval)
sgap = sgap.lo
end
if sgap > 0
info(logger, "λ ≥ $(Float64(trunc(sgap,12)))")
Kazhdan_κ = PropertyT.Kazhdan_from_sgap(sgap, length(sett.S))
Kazhdan_κ = Float64(trunc(Kazhdan_κ, 12))
info(logger, "κ($(sett.name), S) ≥ $Kazhdan_κ: Group HAS property (T)!")
return true
else
sgap = Float64(trunc(sgap, 12))
info(logger, "λ($(sett.name), S) ≥ $sgap: Group may NOT HAVE property (T)!")
return false
end
end
info(logger, "κ($(sett.name), S) ≥ < 0: Tells us nothing about property (T)")
return false
end