Mercurial > repos > public > sbplib_julia
diff src/SbpOperators/volumeops/volume_operator.jl @ 1025:e74c41c4b60e feature/dissipation_operators
Merge refactor/sbpoperators/inflation
author | Jonatan Werpers <jonatan@werpers.com> |
---|---|
date | Mon, 21 Mar 2022 15:12:59 +0100 |
parents | 52f07c77299d |
children | 14cb97284373 05a25a5063bb |
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--- a/src/SbpOperators/volumeops/volume_operator.jl Fri Mar 18 15:44:03 2022 +0100 +++ b/src/SbpOperators/volumeops/volume_operator.jl Mon Mar 21 15:12:59 2022 +0100 @@ -6,28 +6,22 @@ the stencils `inner_stencil` and `closure_stencils`. When `Dim=1`, the corresponding `VolumeOperator` tensor mapping is returned. When `Dim>1`, the returned operator is the appropriate outer product of a one-dimensional -operators and `IdentityMapping`s, e.g for `Dim=3` the volume operator in the +operators and `IdentityTensor`s, e.g for `Dim=3` the volume operator in the y-direction is `I⊗op⊗I`. """ function volume_operator(grid::EquidistantGrid, inner_stencil, closure_stencils, parity, direction) #TODO: Check that direction <= Dim? - # Create 1D volume operator in along coordinate direction op = VolumeOperator(restrict(grid, direction), inner_stencil, closure_stencils, parity) - # Create 1D IdentityMappings for each coordinate direction - one_d_grids = restrict.(Ref(grid), Tuple(1:dimension(grid))) - Is = IdentityMapping{eltype(grid)}.(size.(one_d_grids)) - # Formulate the correct outer product sequence of the identity mappings and - # the volume operator - parts = Base.setindex(Is, op, direction) - return foldl(⊗, parts) + return LazyTensors.inflate(op, size(grid), direction) end +# TBD: Should the inflation happen here or should we remove this method and do it at the caller instead? """ VolumeOperator{T,N,M,K} <: TensorOperator{T,1} Implements a one-dimensional constant coefficients volume operator """ -struct VolumeOperator{T,N,M,K} <: TensorMapping{T,1,1} +struct VolumeOperator{T,N,M,K} <: LazyTensor{T,1,1} inner_stencil::Stencil{T,N} closure_stencils::NTuple{M,Stencil{T,K}} size::NTuple{1,Int} @@ -59,3 +53,4 @@ r = getregion(i, closure_size(op), op.size[1]) return LazyTensors.apply(op, v, Index(i, r)) end +# TODO: Move this to LazyTensors when we have the region communication down.