GroupsWithPropertyT/Orb_AutF4.jl

243 lines
6.7 KiB
Julia

using JLD
using JuMP
using SCS
using GroupRings
using PropertyT
using ArgParse
immutable ProblemData{T}
name::String
Us::Vector{SparseMatrixCSC{Float64,Int}}
Ps::Vector{Array{JuMP.Variable,2}}
cnstr::Vector{T}
laplacian::SparseVector{Float64}
laplacianSq::SparseVector{Float64}
dims::Vector{Int}
end
function sparsify!{T}(U::AbstractArray{T}, eps=eps(T))
# n = rank(U)
U[abs.(U) .< eps] = zero(T)
# @assert rank(U) == n
return sparse(U)
end
sparsify{T}(U::AbstractArray{T}, eps=eps(T)) = sparsify!(deepcopy(U), eps)
small_to_zero!{T}(A::AbstractArray{T}, eps=eps(T)) = A[abs(A) .< eps] = zero(T)
function orbit_spvector(vect::AbstractVector, orbits)
orb_vector = spzeros(length(orbits))
for (i,o) in enumerate(orbits)
k = vect[collect(o)]
val = k[1]
@assert all(k .== val)
orb_vector[i] = val
end
return orb_vector
end
function orbit_constraint(cnstrs::Vector{Vector{Vector{Int64}}}, n)
result = spzeros(n,n)
for cnstr in cnstrs
for p in cnstr
result[p[1],p[2]] += 1.0
end
end
return 1/length(cnstrs)*result
end
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, P[k][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 init_ProblemData(name::String)
splap = load(joinpath(name, "delta.jld"), "delta");
pm = load(joinpath(name, "pm.jld"), "pm");
cnstr = PropertyT.constraints_from_pm(pm);
splap² = GroupRings.mul(splap, splap, pm);
Uπs = load(joinpath(name, "U_pis.jld"), "Uπs");
#dimensions of the corresponding πs:
dims = [1,1,2,3,3,4,4,8,6,6,6,6,4,4,8,1,1,2,3,3]
# dims load(joinpath(name, "U_pis.jld"), "dims")
Uπs = sparsify.(Uπs);
m, P = init_model(Uπs);
orbits = load(joinpath(name, "orbits.jld"), "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)
orb_SOutF4data = ProblemData(name, Uπs, P, orb_spcnstrm, orb_splap, orb_splap², dims);
return m, orb_SOutF4data
end
function transform{T}(U::AbstractArray{T,2}, V::AbstractArray{T,2}, eps=eps(T))
w = U'*V*U
sparsify!(w, eps)
dropzeros!(w)
return w
end
A(data::ProblemData, π, t) = data.dims[π]*transform(data.Us[π], data.cnstr[t])
function constrLHS(m::JuMP.Model, data::ProblemData, 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 addconstraints!(m::JuMP.Model, data::ProblemData, l::Int=length(data.cnstr); var::Symbol = )
λ = getvariable(m, var)
for t in 1:l
d, = data.laplacian[t], data.laplacianSq[t]
lhs = constrLHS(m, data, t)
if lhs == zero(lhs)
if d == 0 && == 0
info("Detected empty constraint")
continue
else
warn("Adding unsatisfiable constraint!")
end
end
JuMP.@constraint(m, lhs == - λ*d)
end
end
function reconstructP(m::JuMP.Model, data::ProblemData)
computedPs = [getvalue(P) for P in data.Ps]
return sum(data.dims[π]*data.Us[π]*computedPs[π]*data.Us[π]' for π in 1:endof(data.Ps))
end
function cpuinfo_physicalcores()
maxcore = -1
for line in eachline("/proc/cpuinfo")
if startswith(line, "core id")
maxcore = max(maxcore, parse(Int, split(line, ':')[2]))
end
end
maxcore < 0 && error("failure to read core ids from /proc/cpuinfo")
return maxcore + 1
end
function parse_commandline()
s = ArgParseSettings()
@add_arg_table s begin
"--tol"
help = "set numerical tolerance for the SDP solver (default: 1e-5)"
arg_type = Float64
default = 1e-5
"--iterations"
help = "set maximal number of iterations for the SDP solver (default: 20000)"
arg_type = Int
default = 20000
"--upper-bound"
help = "Set an upper bound for the spectral gap (default: Inf)"
arg_type = Float64
default = Inf
"--cpus"
help = "Set number of cpus used by solver (default: auto)"
arg_type = Int
required = false
# "-N"
# help = "Consider automorphisms of free group on N generators (default: N=3)"
# arg_type = Int
# default = 2
end
return parse_args(s)
end
function create_SDP_problem(name::String; upper_bound=Inf)
info(PropertyT.logger, "Loading data....")
t = @timed SDP_problem, orb_data = init_ProblemData(name);
info(PropertyT.logger, PropertyT.timed_msg(t))
if upper_bound < Inf
λ = JuMP.getvariable(SDP_problem, )
JuMP.@constraint(SDP_problem, λ <= upper_bound)
end
info(PropertyT.logger, "Adding constraints... ")
t = @timed addconstraints!(SDP_problem, orb_data)
info(PropertyT.logger, PropertyT.timed_msg(t))
return SDP_problem, orb_data
end
function λandP(m::JuMP.Model, data::ProblemData)
info(PropertyT.logger, "Solving SDP problem...")
varλ = JuMP.getvariable(m, )
varP = data.Ps
λ, P = PropertyT.λandP(data.name, m, varλ, varP)
recP = reconstructP(m, data)
fname = PropertyT.λSDPfilenames(data.name)[2]
save(fname, "origP", P, "P", recP)
return λ, recP
end
function main()
name = "SOutF4_E4"
if !isdir(name)
throw("Create dir with all the required orbit data first!")
end
logger = PropertyT.setup_logging(name)
parsed_args = parse_commandline()
if parsed_args["cpus"] != nothing
if parsed_args["cpus"] > cpuinfo_physicalcores()
warn("Number of specified cores exceeds the physical core cound. Performance will suffer.")
end
Blas.set_num_threads(parsed_args["cpus"])
end
tol = parsed_args["tol"]
iterations = parsed_args["iterations"]
upper_bound = parsed_args["upper-bound"]
solver = SCS.SCSSolver(eps=tol, max_iters=iterations, verbose=true, linearsolver=SCS.Indirect)
fnames = PropertyT.λSDPfilenames(name)
if all(isfile.(fnames)) && false
λ, P = PropertyT.λandP(name)
else
info(logger, "Creating SDP problem...")
SDP_problem, orb_data = create_SDP_problem(name, upper_bound=upper_bound)
JuMP.setsolver(SDP_problem, solver)
λ, P = λandP(SDP_problem, orb_data)
end
info(PropertyT.logger, "λ = ")
info(PropertyT.logger, "sum(P) = $(sum(P))")
info(PropertyT.logger, "maximum(P) = $(maximum(P))")
info(PropertyT.logger, "minimum(P) = $(minimum(P))")
end
main()