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https://github.com/kalmarek/PropertyT.jl.git
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Merge remote-tracking branch 'origin/enh/warmstart' into enh/warmstart-0.6
# Conflicts: # src/OrbitDecomposition.jl
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commit
10808583e3
@ -3,14 +3,14 @@ using SCS
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export Settings, OrbitData
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export Settings, OrbitData
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immutable Settings
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immutable Settings{T<:AbstractMathProgSolver}
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name::String
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name::String
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N::Int
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N::Int
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G::Group
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G::Group
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S::Vector
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S::Vector
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autS::Group
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autS::Group
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radius::Int
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radius::Int
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solver::SCSSolver
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solver::T
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upper_bound::Float64
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upper_bound::Float64
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tol::Float64
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tol::Float64
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end
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end
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@ -37,11 +37,13 @@ function OrbitData(sett::Settings)
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splap² = similar(splap)
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splap² = similar(splap)
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splap² = GroupRings.mul!(splap², splap, splap, pm);
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splap² = GroupRings.mul!(splap², splap, splap, pm);
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# Uπs = load(joinpath(name, "U_pis.jld"), "Uπs");
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Uπs = load(joinpath(prepath(sett), "U_pis.jld"), "Uπs")
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Uπs = load(joinpath(prepath(sett), "U_pis.jld"), "Uπs")
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nzros = [i for i in 1:length(Uπs) if size(Uπs[i],2) !=0]
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Uπs = Uπs[nzros]
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Uπs = sparsify!.(Uπs, sett.tol, check=true, verbose=true)
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Uπs = sparsify!.(Uπs, sett.tol, check=true, verbose=true)
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#dimensions of the corresponding πs:
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#dimensions of the corresponding πs:
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dims = load(joinpath(prepath(sett), "U_pis.jld"), "dims")
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dims = load(joinpath(prepath(sett), "U_pis.jld"), "dims")[nzros]
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m, P = init_model(size(Uπs,1), [size(U,2) for U in Uπs]);
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m, P = init_model(size(Uπs,1), [size(U,2) for U in Uπs]);
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@ -136,13 +136,8 @@ function perm_reps(S::Vector, autS::Group, radius::Int)
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return perm_reps(autS, E)
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return perm_reps(autS, E)
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end
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end
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function reconstruct_sol{T<:GroupElem}(preps::Dict{T, Generic.perm},
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function reconstruct_sol{T<:GroupElem, S<:Nemo.perm}(preps::Dict{T, S},
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aUs::Vector, aPs::Vector, adims::Vector)
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Us::Vector, Ps::Vector, dims::Vector)
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idx = [π for π in 1:length(aUs) if size(aUs[π], 2) != 0]
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Us = aUs[idx]
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Ps = aPs[idx]
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dims = adims[idx];
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l = length(Us)
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l = length(Us)
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transfP = [dims[π].*Us[π]*Ps[π]*Us[π]' for π in 1:l]
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transfP = [dims[π].*Us[π]*Ps[π]*Us[π]' for π in 1:l]
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@ -22,6 +22,11 @@ end
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Nemo.isone(p::GroupElem) = p == parent(p)()
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Nemo.isone(p::GroupElem) = p == parent(p)()
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function Nemo.dim(χ::PropertyT.PermCharacter)
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G = PermutationGroup(sum(χ.p))
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return χ(G())
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end
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## NOTE: this works only for Z/2!!!!
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## NOTE: this works only for Z/2!!!!
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function (chi::DirectProdCharacter)(g::DirectProductGroupElem)
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function (chi::DirectProdCharacter)(g::DirectProductGroupElem)
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return reduce(*, 1, ((-1)^isone(g.elts[j]) for j in 1:chi.i))
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return reduce(*, 1, ((-1)^isone(g.elts[j]) for j in 1:chi.i))
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@ -137,16 +137,12 @@ function λandP(name::String)
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end
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end
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function λandP(name::String, SDP_problem::JuMP.Model, varλ, varP)
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function λandP(name::String, SDP_problem::JuMP.Model, varλ, varP)
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if exists(joinpath(name, "solver.log"))
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rm(joinpath(name, "solver.log"))
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end
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add_handler(solver_logger,
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add_handler(solver_logger,
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DefaultHandler(joinpath(name, "solver_$(string(now())).log"),
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DefaultHandler(joinpath(name, "solver_$(string(now())).log"),
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DefaultFormatter("{date}| {msg}")),
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DefaultFormatter("{date}| {msg}")),
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"solver_log")
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"solver_log")
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λ, P = compute_λandP(SDP_problem, varλ, varP)
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λ, P, warmstart = compute_λandP(SDP_problem, varλ, varP)
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remove_handler(solver_logger, "solver_log")
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remove_handler(solver_logger, "solver_log")
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@ -155,6 +151,8 @@ function λandP(name::String, SDP_problem::JuMP.Model, varλ, varP)
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if λ > 0
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if λ > 0
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save(λ_fname, "λ", λ)
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save(λ_fname, "λ", λ)
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save(P_fname, "P", P)
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save(P_fname, "P", P)
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@show warmstart[1]
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save(joinpath(name, "warmstart.jld"), "warmstart", warmstart)
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else
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else
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throw(ErrorException("Solver did not produce a valid solution!: λ = $λ"))
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throw(ErrorException("Solver did not produce a valid solution!: λ = $λ"))
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end
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end
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@ -162,7 +160,7 @@ function λandP(name::String, SDP_problem::JuMP.Model, varλ, varP)
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end
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end
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function compute_λandP(m, varλ, varP)
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function compute_λandP(m, varλ, varP; warmstart=nothing)
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λ = 0.0
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λ = 0.0
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P = nothing
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P = nothing
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while λ == 0.0
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while λ == 0.0
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@ -170,11 +168,16 @@ function compute_λandP(m, varλ, varP)
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solve_SDP(m)
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solve_SDP(m)
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λ = JuMP.getvalue(varλ)
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λ = JuMP.getvalue(varλ)
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P = JuMP.getvalue(varP)
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P = JuMP.getvalue(varP)
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p_sol = m.internalModel.primal_sol
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d_sol = m.internalModel.dual_sol
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s = m.internalModel.slack
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catch y
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catch y
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warn(solver_logger, y)
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warn(solver_logger, y)
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end
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end
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end
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end
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return λ, P
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return λ, P, (p_sol, d_sol, s)
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end
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end
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Kazhdan_from_sgap(λ,N) = sqrt(2*λ/N)
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Kazhdan_from_sgap(λ,N) = sqrt(2*λ/N)
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