Mercurial > repos > public > sbplib_julia
view src/Grids/tensor_grid.jl @ 1337:f265799bc2b6 refactor/grids
Remove some comments
author | Jonatan Werpers <jonatan@werpers.com> |
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date | Thu, 04 May 2023 08:38:48 +0200 |
parents | ed3ea0630825 |
children | 5604676d8426 |
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""" TensorGrid{T,D} <: Grid{T,D} * Only supports HasShape grids at the moment # TODO: """ struct TensorGrid{T,D,GT<:NTuple{N,Grid} where N} <: Grid{T,D} grids::GT function TensorGrid(gs...) T = mapreduce(eltype, combined_coordinate_vector_type, gs) D = sum(ndims, gs) return new{T,D,typeof(gs)}(gs) end end # Indexing interface function Base.getindex(g::TensorGrid, I...) szs = ndims.(g.grids) Is = LazyTensors.split_tuple(I, szs) ps = map((g,I)->SVector(g[I...]), g.grids, Is) return vcat(ps...) end function Base.eachindex(g::TensorGrid) szs = LazyTensors.concatenate_tuples(size.(g.grids)...) return CartesianIndices(szs) end # Iteration interface Base.iterate(g::TensorGrid) = iterate(Iterators.product(g.grids...)) |> _iterate_combine_coords Base.iterate(g::TensorGrid, state) = iterate(Iterators.product(g.grids...), state) |> _iterate_combine_coords _iterate_combine_coords(::Nothing) = nothing _iterate_combine_coords((next,state)) = combine_coordinates(next...), state Base.IteratorSize(::Type{<:TensorGrid{<:Any, D}}) where D = Base.HasShape{D}() Base.eltype(::Type{<:TensorGrid{T}}) where T = T Base.length(g::TensorGrid) = sum(length, g.grids) Base.size(g::TensorGrid) = LazyTensors.concatenate_tuples(size.(g.grids)...) refine(g::TensorGrid, r::Int) = mapreduce(g->refine(g,r), TensorGrid, g.grids) coarsen(g::TensorGrid, r::Int) = mapreduce(g->coarsen(g,r), TensorGrid, g.grids) """ TensorGridBoundary{N, BID} <: BoundaryIdentifier # TODO: """ struct TensorGridBoundary{N, BID} <: BoundaryIdentifier end grid_id(::TensorGridBoundary{N, BID}) where {N, BID} = N boundary_id(::TensorGridBoundary{N, BID}) where {N, BID} = BID() """ boundary_identifiers(::TensorGrid) Returns a tuple containing the boundary identifiers for the grid. """ function boundary_identifiers(g::TensorGrid) per_grid = map(eachindex(g.grids)) do i return map(bid -> TensorGridBoundary{i, typeof(bid)}(), boundary_identifiers(g.grids[i])) end return LazyTensors.concatenate_tuples(per_grid...) end """ boundary_grid(grid::TensorGrid, id::TensorGridBoundary) The grid for the boundary specified by `id`. """ function boundary_grid(g::TensorGrid, bid::TensorGridBoundary) local_boundary_grid = boundary_grid(g.grids[grid_id(bid)], boundary_id(bid)) new_grids = Base.setindex(g.grids, local_boundary_grid, grid_id(bid)) return TensorGrid(new_grids...) end function combined_coordinate_vector_type(coordinate_types...) combined_coord_length = mapreduce(_ncomponents, +, coordinate_types) combined_coord_type = mapreduce(eltype, promote_type, coordinate_types) if combined_coord_length == 1 return combined_coord_type else return SVector{combined_coord_length, combined_coord_type} end end function combine_coordinates(coords...) return mapreduce(SVector, vcat, coords) end