PropertyT.jl/src/orbitdata.jl

225 lines
6.5 KiB
Julia

###############################################################################
#
# OrbitData
#
###############################################################################
struct OrbitData{T<:AbstractArray{Float64, 2}, GEl<:GroupElem, P<:perm}
orbits::Vector{Vector{Int}}
preps::Dict{GEl, P}
Uπs::Vector{T}
dims::Vector{Int}
end
function OrbitData(RG::GroupRing, autS::Group)
orbs = orbit_decomposition(autS, RG.basis, RG.basis_dict)
@assert sum(length(o) for o in orbs) == length(RG.basis)
autS_mps = Projections.rankOne_projections(GroupRing(autS))
preps = perm_reps(autS, RG.basis[1:size(RG.pm,1)], RG.basis_dict)
mreps = matrix_reps(preps)
Uπs = [orthSVD(matrix_repr(p, mreps)) for p in autS_mps]
multiplicities = size.(Uπs,2)
dimensions = [Int(p[autS()]*Int(order(autS))) for p in autS_mps]
@assert dot(multiplicities, dimensions) == size(RG.pm,1)
nzros = [i for i in 1:length(Uπs) if size(Uπs[i],2) !=0]
return OrbitData(orbs, preps, Uπs[nzros], dims[nzros])
end
function compute_OrbitData(RG::GroupRing, autS::Group)
info("Decomposing E into orbits of $(autS)")
@time orbs = orbit_decomposition(autS, RG.basis, RG.basis_dict)
@assert sum(length(o) for o in orbs) == length(RG.basis)
info("E consists of $(length(orbs)) orbits!")
info("Action matrices")
@time preps = perm_reps(autS, RG.basis[1:size(RG.pm,1)], RG.basis_dict)
mreps = matrix_reps(preps)
info("Projections")
@time autS_mps = Projections.rankOne_projections(GroupRing(autS));
info("Uπs...")
@time Uπs = [orthSVD(matrix_repr(p, mreps)) for p in autS_mps]
multiplicities = size.(Uπs,2)
info("multiplicities = $multiplicities")
dimensions = [Int(p[autS()]*Int(order(autS))) for p in autS_mps];
info("dimensions = $dimensions")
@assert dot(multiplicities, dimensions) == size(RG.pm,1)
return OrbitData(orbs, preps, Uπs, dimensions)
end
function decimate(od::OrbitData)
nzros = [i for i in 1:length(od.Uπs) if size(od.Uπs[i],2) !=0]
Us = map(x -> PropertyT.sparsify!(x, eps(Float64)*1e3, verbose=true), od.Uπs[nzros])
#dimensions of the corresponding πs:
dims = od.dims[nzros]
return OrbitData(od.orbits, od.preps, full.(Us), dims);
end
function save_OrbitData(sett::Settings, data::OrbitData)
save_preps(filename(prepath(sett), :preps), data.preps)
save(filename(prepath(sett), :orbits),
"orbits", data.orbits)
save(filename(prepath(sett), :Uπs),
"Uπs", data.Uπs,
"dims", data.dims)
end
function load_OrbitData(sett::Settings)
info("Loading Uπs, dims, orbits...")
Uπs = load(filename(prepath(sett), :Uπs), "Uπs")
nzros = [i for i in 1:length(Uπs) if size(Uπs[i],2) !=0]
Uπs = map(x -> sparsify!(x, sett.tol/100, verbose=true), Uπs)
#dimensions of the corresponding πs:
dims = load(filename(prepath(sett), :Uπs), "dims")
orbits = load(filename(prepath(sett), :orbits), "orbits")
preps = load_preps(filename(prepath(sett), :preps), sett.autS)
return OrbitData(orbits, preps, Uπs, dims)
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)))
save(fname, "perms_d", [preps[elt].d for elt in elements(autS)])
end
function orthSVD(M::AbstractMatrix{T}) where {T<:AbstractFloat}
M = full(M)
fact = svdfact(M)
M_rank = sum(fact[:S] .> maximum(size(M))*eps(T))
return fact[:U][:,1:M_rank]
end
function orbit_decomposition(G::Group, E::Vector, rdict=GroupRings.reverse_dict(E))
elts = collect(elements(G))
tovisit = trues(E);
orbits = Vector{Vector{Int}}()
orbit = zeros(Int, length(elts))
for i in 1:endof(E)
if tovisit[i]
g = E[i]
Threads.@threads for j in 1:length(elts)
orbit[j] = rdict[elts[j](g)]
end
tovisit[orbit] = false
push!(orbits, unique(orbit))
end
end
return orbits
end
###############################################################################
#
# Sparsification
#
###############################################################################
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)
###############################################################################
#
# perm-, matrix-, representations
#
###############################################################################
function perm_repr(g::GroupElem, E::Vector, E_dict)
p = Vector{Int}(length(E))
for (i,elt) in enumerate(E)
p[i] = E_dict[g(elt)]
end
return p
end
function perm_reps(G::Group, E::Vector, E_rdict=GroupRings.reverse_dict(E))
elts = collect(elements(G))
l = length(elts)
preps = Vector{perm}(l)
permG = PermutationGroup(length(E))
Threads.@threads for i in 1:l
preps[i] = permG(PropertyT.perm_repr(elts[i], E, E_rdict), false)
end
return Dict(elts[i]=>preps[i] for i in 1:l)
end
function matrix_repr(x::GroupRingElem, mreps::Dict)
nzeros = findn(x.coeffs)
return sum(x[i].*mreps[parent(x).basis[i]] for i in nzeros)
end
function matrix_reps(preps::Dict{T,perm{I}}) where {T<:GroupElem, I<:Integer}
kk = collect(keys(preps))
mreps = Vector{SparseMatrixCSC{Float64, Int}}(length(kk))
Threads.@threads for i in 1:length(kk)
mreps[i] = AbstractAlgebra.matrix_repr(preps[kk[i]])
end
return Dict(kk[i] => mreps[i] for i in 1:length(kk))
end