Added tests for polytopal coarsening

Author: JordiManyer

src/Geometry.jl

@@ -457,7 +457,7 @@ function Geometry.DiscreteModel(
   @assert size(cell_graph,1) == ncells
   @assert size(cell_graph,2) == ncells
 
-  lcell_to_cell, lcell_to_part, gid_to_part = map(parts) do part
+  lcell_to_cell, lcell_to_part = map(parts) do part
     cell_to_mask = fill(false,ncells)
     icell_to_jcells_ptrs = cell_graph.colptr
     icell_to_jcells_data = cell_graph.rowval
@@ -473,9 +473,8 @@ function Geometry.DiscreteModel(
       end
     end
     lcell_to_cell = findall(cell_to_mask)
-    lcell_to_part = zeros(Int32,length(lcell_to_cell))
-    lcell_to_part .= cell_to_part[lcell_to_cell]
-    lcell_to_cell, lcell_to_part, cell_to_part
+    lcell_to_part = collect(Int32,view(cell_to_part,lcell_to_cell))
+    lcell_to_cell, lcell_to_part
   end |> tuple_of_arrays
 
   partition = map(parts,lcell_to_cell,lcell_to_part) do part, lcell_to_cell, lcell_to_part
@@ -509,6 +508,15 @@ function Geometry.UnstructuredDiscreteModel(model::GenericDistributedDiscreteMod
   )
 end
 
+# PolytopalDiscreteModel
+
+function Geometry.PolytopalDiscreteModel(model::GenericDistributedDiscreteModel)
+  return GenericDistributedDiscreteModel(
+    map(Geometry.PolytopalDiscreteModel,local_views(model)),
+    get_cell_gids(model)
+  )
+end
+
 # Simplexify
 
 function Geometry.simplexify(model::DistributedDiscreteModel;kwargs...)

test/PolytopalCoarseningTests.jl

@@ -0,0 +1,36 @@
+module PolytopalCoarseningTests
+
+using Gridap
+using GridapDistributed, PartitionedArrays
+
+using Gridap.Adaptivity, Gridap.Geometry, Gridap.Arrays
+using Gridap.ReferenceFEs
+
+function distributed_voronoi(ranks,np,nc,domain)
+  serial_model = Geometry.voronoi(simplexify(CartesianDiscreteModel(domain,nc)))
+  cell_to_rank = zeros(Int,num_cells(serial_model))
+  for (r,cells) in enumerate(uniform_partition(1:prod(np),np,nc .+ 1))
+    cell_to_rank[cells] .= r
+  end
+  return DiscreteModel(ranks,serial_model,cell_to_rank)
+end
+
+np = (2,2)
+ranks = with_mpi() do distribute
+  distribute(LinearIndices((prod(np),)))
+end
+
+Dc = 2
+fmodel = distributed_voronoi(ranks,np,(8,8),(0,1,0,1))
+writevtk(fmodel,"tmp/fmodel")
+
+fgids = partition(get_cell_gids(fmodel))
+patch_cells = map(fgids) do fids
+  Table([collect(own_to_local(fids))])
+end
+ptopo = Geometry.PatchTopology(get_grid_topology(fmodel), patch_cells)
+
+cmodel, glues = Adaptivity.coarsen(fmodel,ptopo; return_glue=true)
+writevtk(cmodel, "tmp/cmodel")
+
+end # module