juliasmoothoptimizers / cannoles.jl Goto Github PK

using Gridap, PDENLPModels

  # Definition of the domain
  n = 100
  domain = (-1, 1, -1, 1)
  partition = (n, n)
  model = CartesianDiscreteModel(domain, partition)

  # Definition of the spaces:
  valuetype = Float64
  reffe = ReferenceFE(lagrangian, valuetype, 2)
  Xpde = TestFESpace(model, reffe; conformity = :H1, dirichlet_tags = "boundary")
  y0(x) = 0.0
  Ypde = TrialFESpace(Xpde, y0)

  reffe_con = ReferenceFE(lagrangian, valuetype, 1)
  Xcon = TestFESpace(model, reffe_con; conformity = :H1)
  Ycon = TrialFESpace(Xcon)
  Y = MultiFieldFESpace([Ypde, Ycon])

  # Integration machinery
  trian = Triangulation(model)
  degree = 1
  dΩ = Measure(trian, degree)

  # Objective function:
  yd(x) = -x[1]^2
  α = 1e-2
  function f(y, u)
    ∫(0.5 * (yd - y) * (yd - y) + 0.5 * α * u * u) * dΩ
  end

  # Definition of the constraint operator
  ω = π - 1 / 8
  h(x) = -sin(ω * x[1]) * sin(ω * x[2])
  function res(y, u, v)
    ∫(∇(v) ⊙ ∇(y) - v * u - v * h) * dΩ
  end
  op = FEOperator(res, Y, Xpde)
  npde = Gridap.FESpaces.num_free_dofs(Ypde)
  ncon = Gridap.FESpaces.num_free_dofs(Ycon)
  x0 = zeros(npde + ncon)
  nlp = GridapPDENLPModel(x0, f, trian, Ypde, Ycon, Xpde, Xcon, op, name = "Control elastic membrane")

using CaNNOLeS, NLPModelsModifiers
nls = FeasibilityResidual(nlp)
stats_cannoles = cannoles(nls)

┌ Warning: linsolve ma57 not available. Using :ldlfactorizations instead
└ @ CaNNOLeS .julia\packages\CaNNOLeS\CGoHr\src\CaNNOLeS.jl:60
[ Info:      I      #F        fx        Δt      ‖∇L‖  ‖Fx - r‖    ‖c(x)‖         α         η         ρ         δ   in_it     nbk  
[ Info:      0       2   2.2e-04   0.0e+00   1.6e-07   0.0e+00   0.0e+00
ERROR: LoadError: AssertionError: LDLT.factor != nothing
Stacktrace:
 [1] newton_system(x::Vector{Float64}, r::Vector{Float64}, λ::Vector{Float64}, Fx::Vector{Float64}, rhs::Vector{Float64}, LDLT::CaNNOLeS.LDLFactStruct, ρold::Float64, params::Dict{Symbol, Float64}, method::Symbol, linsolve::Symbol)
   @ CaNNOLeS .julia\packages\CaNNOLeS\CGoHr\src\CaNNOLeS.jl:616
 [2] cannoles(nls::FeasibilityResidual{Float64, Vector{Float64}}; x::Vector{Float64}, λ::Vector{Float64}, method::Symbol, merit::Symbol, linsolve::Symbol, max_f::Int64, max_time::Float64, max_inner::Int64, ϵtol::Float64, check_small_residual::Bool, always_accept_extrapolation::Bool, ϵkchoice::Symbol, δdec::Float64)
   @ CaNNOLeS .julia\packages\CaNNOLeS\CGoHr\src\CaNNOLeS.jl:315
 [3] cannoles(nls::FeasibilityResidual{Float64, Vector{Float64}})
   @ CaNNOLeS .julia\packages\CaNNOLeS\CGoHr\src\CaNNOLeS.jl:50

  [5a1c9e79] CaNNOLeS v0.5.3
  [56d4f2e9] Gridap v0.15.5
  [40e66cde] LDLFactorizations v0.8.1
  [a4795742] NLPModels v0.18.1
  [e01155f1] NLPModelsModifiers v0.5.1
  [80da258d] PDENLPModels v0.3.0