Mercurial > repos > public > sbplib_julia
view SbpOperators/src/Quadrature.jl @ 300:b00eea62c78e
Create 1D tensor mapping for diagonal norm quadratures, and make the multi-dimensional quadrature use those. Move Qudrature from laplace.jl into Quadrature.jl
author | Vidar Stiernström <vidar.stiernstrom@it.uu.se> |
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date | Tue, 23 Jun 2020 17:32:54 +0200 |
parents | |
children | 417b767c847f |
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# At the moment the grid property is used all over. It could possibly be removed if we implement all the 1D operators as TensorMappings """ Quadrature{Dim,T<:Real,N,M,K} <: TensorMapping{T,Dim,Dim} Implements the quadrature operator `Q` of Dim dimension as a TensorMapping The multi-dimensional tensor operator consists of a tuple of 1D DiagonalQuadrature tensor operators. """ struct Quadrature{Dim,T<:Real,N,M} <: TensorOperator{T,Dim} H::NTuple{Dim,DiagonalQuadrature{T,N,M}} end export Quadrature LazyTensors.domain_size(Q::Quadrature{Dim}, range_size::NTuple{Dim,Integer}) where Dim = range_size function LazyTensors.apply(Q::Quadrature{Dim,T}, v::AbstractArray{T,Dim}, I::NTuple{Dim,Index}) where {T,Dim} error("not implemented") end LazyTensors.apply_transpose(Q::Quadrature{Dim,T}, v::AbstractArray{T,2}, I::NTuple{2,Index}) where {Dim,T} = LazyTensors.apply(Q,v,I) @inline function LazyTensors.apply(Q::Quadrature{1,T}, v::AbstractVector{T}, I::NTuple{1,Index}) where T @inbounds q = apply(Q.H[1], v , I[1]) return q end @inline function LazyTensors.apply(Q::Quadrature{2,T}, v::AbstractArray{T,2}, I::NTuple{2,Index}) where T # Quadrature in x direction @inbounds vx = view(v, :, Int(I[2])) @inbounds qx = apply(Q.H[1], vx , I[1]) # Quadrature in y-direction @inbounds vy = view(v, Int(I[1]), :) @inbounds qy = apply(Q.H[2], vy, I[2]) return qx*qy end """ Quadrature{Dim,T<:Real,N,M,K} <: TensorMapping{T,Dim,Dim} Implements the quadrature operator `H` of Dim dimension as a TensorMapping """ struct DiagonalQuadrature{T<:Real,N,M} <: TensorOperator{T,1} h::T # The grid spacing could be included in the stencil already. Preferable? closure::NTuple{M,T} #TODO: Write a nice constructor end @inline function LazyTensors.apply(H::DiagonalQuadrature{T}, v::AbstractVector{T}, I::NTuple{1,Index}) where T return @inbounds apply(H, v, I[1]) end LazyTensors.apply_transpose(H::Quadrature{Dim,T}, v::AbstractArray{T,2}, I::NTuple{2,Index}) where T = LazyTensors.apply(H,v,I) @inline LazyTensors.apply(H::DiagonalQuadrature, v::AbstractVector{T}, i::Index{Lower}) where T return @inbounds H.h*H.closure[Int(i)]*v[Int(i)] end @inline LazyTensors.apply(H::DiagonalQuadrature,v::AbstractVector{T}, i::Index{Upper}) where T N = length(v); return @inbounds H.h*H.closure[N-Int(i)+1]v[Int(i)] end @inline LazyTensors.apply(H::DiagonalQuadrature, v::AbstractVector{T}, i::Index{Interior}) where T return @inbounds H.h*v[Int(i)] end function LazyTensors.apply(H::DiagonalQuadrature, v::AbstractVector{T}, index::Index{Unknown}) where T N = length(v); r = getregion(Int(index), closuresize(H), N) i = Index(Int(index), r) return LazyTensors.apply(H, v, i) end export LazyTensors.apply function closuresize(H::DiagonalQuadrature{T<:Real,N,M}) where {T,N,M} return M end