Mercurial > repos > public > sbplib_julia
view src/SbpOperators/quadrature/inverse_quadrature.jl @ 483:d5032c58c67a feature/compose_identity_mappings
Actually extend the showerror function
author | Jonatan Werpers <jonatan@werpers.com> |
---|---|
date | Thu, 05 Nov 2020 10:35:07 +0100 |
parents | 0546cb279fc2 |
children | 011ca1639153 |
line wrap: on
line source
export InverseQuadrature """ InverseQuadrature{Dim,T<:Real,M,K} <: TensorMapping{T,Dim,Dim} Implements the inverse quadrature operator `Qi` of Dim dimension as a TensorMapping The multi-dimensional tensor operator consists of a tuple of 1D InverseDiagonalInnerProduct tensor operators. """ struct InverseQuadrature{Dim,T<:Real,M} <: TensorMapping{T,Dim,Dim} Hi::NTuple{Dim,InverseDiagonalInnerProduct{T,M}} end function InverseQuadrature(g::EquidistantGrid{Dim}, quadratureClosure) where Dim Hi = () for i ∈ 1:Dim Hi = (Hi..., InverseDiagonalInnerProduct(restrict(g,i), quadratureClosure)) end return InverseQuadrature(Hi) end LazyTensors.range_size(Hi::InverseQuadrature) = getindex.(range_size.(Hi.Hi),1) LazyTensors.domain_size(Hi::InverseQuadrature) = getindex.(domain_size.(Hi.Hi),1) LazyTensors.domain_size(Qi::InverseQuadrature{Dim}, range_size::NTuple{Dim,Integer}) where Dim = range_size function LazyTensors.apply(Qi::InverseQuadrature{Dim,T}, v::AbstractArray{T,Dim}, I::Vararg{Index,Dim}) where {T,Dim} error("not implemented") end @inline function LazyTensors.apply(Qi::InverseQuadrature{1,T}, v::AbstractVector{T}, I::Index) where T @inbounds q = apply(Qi.Hi[1], v , I) return q end @inline function LazyTensors.apply(Qi::InverseQuadrature{2,T}, v::AbstractArray{T,2}, I::Index, J::Index) where T # InverseQuadrature in x direction @inbounds vx = view(v, :, Int(J)) @inbounds qx_inv = apply(Qi.Hi[1], vx , I) # InverseQuadrature in y-direction @inbounds vy = view(v, Int(I), :) @inbounds qy_inv = apply(Qi.Hi[2], vy, J) return qx_inv*qy_inv end LazyTensors.apply_transpose(Qi::InverseQuadrature{Dim,T}, v::AbstractArray{T,Dim}, I::Vararg{Index,Dim}) where {Dim,T} = LazyTensors.apply(Qi,v,I...)