Mercurial > repos > public > sbplib_julia
diff SbpOperators/src/constantlaplace.jl @ 291:0f94dc29c4bf
Merge in branch boundary_conditions
author | Jonatan Werpers <jonatan@werpers.com> |
---|---|
date | Mon, 22 Jun 2020 21:43:05 +0200 |
parents | dd621017b695 |
children | 3747e5636eef |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/SbpOperators/src/constantlaplace.jl Mon Jun 22 21:43:05 2020 +0200 @@ -0,0 +1,54 @@ +#TODO: Naming?! What is this? It is a 1D tensor operator but what is then the +# potentially multi-D laplace tensor mapping then? +# Ideally I would like the below to be the laplace operator in 1D, while the +# multi-D operator is a a tuple of the 1D-operator. Possible via recursive +# definitions? Or just bad design? +""" + ConstantLaplaceOperator{T<:Real,N,M,K} <: TensorOperator{T,1} +Implements the Laplace tensor operator `L` with constant grid spacing and coefficients +in 1D dimension +""" +struct ConstantLaplaceOperator{T<:Real,N,M,K} <: TensorOperator{T,1} + h_inv::T # The grid spacing could be included in the stencil already. Preferable? + a::T # TODO: Better name? + innerStencil::Stencil{T,N} + closureStencils::NTuple{M,Stencil{T,K}} + parity::Parity + #TODO: Write a nice constructor +end + +@enum Parity begin + odd = -1 + even = 1 +end + +LazyTensors.domain_size(L::ConstantLaplaceOperator, range_size::NTuple{1,Integer}) = range_size + +function LazyTensors.apply(L::ConstantLaplaceOperator{T}, v::AbstractVector{T}, I::NTuple{1,Index}) where T + return apply(L, v, I[1]) +end + +# Apply for different regions Lower/Interior/Upper or Unknown region +@inline function LazyTensors.apply(L::ConstantLaplaceOperator, v::AbstractVector, i::Index{Lower}) + return @inbounds L.a*L.h_inv*L.h_inv*apply_stencil(L.closureStencils[Int(i)], v, Int(i)) +end + +@inline function LazyTensors.apply(L::ConstantLaplaceOperator, v::AbstractVector, i::Index{Interior}) + return @inbounds L.a*L.h_inv*L.h_inv*apply_stencil(L.innerStencil, v, Int(i)) +end + +@inline function LazyTensors.apply(L::ConstantLaplaceOperator, v::AbstractVector, i::Index{Upper}) + N = length(v) # TODO: Use domain_size here instead? + return @inbounds L.a*L.h_inv*L.h_inv*Int(L.parity)*apply_stencil_backwards(L.closureStencils[N-Int(i)+1], v, Int(i)) +end + +@inline function LazyTensors.apply(L::ConstantLaplaceOperator, v::AbstractVector, index::Index{Unknown}) + N = length(v) # TODO: Use domain_size here instead? + r = getregion(Int(index), closuresize(L), N) + i = Index(Int(index), r) + return apply(L, v, i) +end + +function closuresize(L::ConstantLaplaceOperator{T<:Real,N,M,K}) where T,N,M,K + return M +end