distributed diffable trian MWE

scripts/Embedded/MWEs/distributed_differentiable_trian.jl

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+using GridapTopOpt
+using Gridap
+
+using GridapDistributed, PartitionedArrays
+
+using GridapEmbedded
+using GridapEmbedded.LevelSetCutters
+using Gridap.Geometry, Gridap.FESpaces, Gridap.CellData, Gridap.Adaptivity
+
+using GridapTopOpt: get_subfacet_normal_vector, get_ghost_normal_vector
+using GridapTopOpt: get_conormal_vector, get_tangent_vector
+
+order = 1
+n = 16
+
+parts = (2,2)
+ranks = DebugArray(LinearIndices((prod(parts),)))
+
+_model = CartesianDiscreteModel(ranks,parts,(0,1,0,1),(n,n))
+# _model = CartesianDiscreteModel((0,1,0,1),(n,n))
+
+base_model = UnstructuredDiscreteModel(_model)
+ref_model = refine(base_model, refinement_method = "barycentric")
+model = Gridap.Adaptivity.get_model(ref_model)
+
+reffe = ReferenceFE(lagrangian,Float64,order)
+V_φ = TestFESpace(model,reffe)
+
+φh = interpolate(x->sqrt((x[1]-0.5)^2+(x[2]-0.5)^2)-0.5223,V_φ) # Circle
+fh = interpolate(x->cos(x[1]*x[2]),V_φ)
+
+geo = DiscreteGeometry(φh,model)
+cutgeo = cut(model,geo)
+
+Ωin = Triangulation(cutgeo,PHYSICAL_IN)
+Ω_AD = DifferentiableTriangulation(Ωin,V_φ)
+dΩ = Measure(Ω_AD,2*order)
+
+Γ = EmbeddedBoundary(cutgeo)
+dΓ = Measure(Γ,2*order)
+
+J_bulk(φ) = ∫(fh)dΩ
+dJ_bulk_AD = gradient(J_bulk,φh)
+dJ_bulk_AD_vec = assemble_vector(dJ_bulk_AD,V_φ)
+
+dJ_bulk_exact(q) = ∫(-fh*q/(norm ∘ (∇(φh))))dΓ
+dJ_bulk_exact_vec = assemble_vector(dJ_bulk_exact,V_φ)
+
+norm(dJ_bulk_AD_vec - dJ_bulk_exact_vec) < 1e-10