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annotate SbpOperators/src/Quadrature.jl @ 325:41c3c25e4e3b

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LazyTensors: Simplify the LazyElementwiseOperation type by restricting it and introducing a LazyConstantArray to handle scalars.
author Jonatan Werpers <jonatan@werpers.com>
date Thu, 24 Sep 2020 22:31:04 +0200
parents 777063b6f049
children
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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
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1 # At the moment the grid property is used all over. It could possibly be removed if we implement all the 1D operators as TensorMappings
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2 """
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3 Quadrature{Dim,T<:Real,N,M,K} <: TensorMapping{T,Dim,Dim}
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5 Implements the quadrature operator `Q` of Dim dimension as a TensorMapping
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6 The multi-dimensional tensor operator consists of a tuple of 1D DiagonalNorm H
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7 tensor operators.
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8 """
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9 export Quadrature
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10 struct Quadrature{Dim,T<:Real,N,M} <: TensorOperator{T,Dim}
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11 H::NTuple{Dim,DiagonalNorm{T,N,M}}
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12 end
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14 LazyTensors.domain_size(Q::Quadrature{Dim}, range_size::NTuple{Dim,Integer}) where Dim = range_size
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16 function LazyTensors.apply(Q::Quadrature{Dim,T}, v::AbstractArray{T,Dim}, I::Vararg{Index,Dim}) where {T,Dim}
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17 error("not implemented")
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18 end
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20 LazyTensors.apply_transpose(Q::Quadrature{Dim,T}, v::AbstractArray{T,Dim}, I::Vararg{Index,Dim}) where {Dim,T} = LazyTensors.apply(Q,v,I)
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22 @inline function LazyTensors.apply(Q::Quadrature{1,T}, v::AbstractVector{T}, I::Index) where T
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23 @inbounds q = apply(Q.H[1], v , I)
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24 return q
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25 end
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27 @inline function LazyTensors.apply(Q::Quadrature{2,T}, v::AbstractArray{T,2}, I::Index, J::Index) where T
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28 # Quadrature in x direction
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29 @inbounds vx = view(v, :, Int(J))
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30 @inbounds qx = apply(Q.H[1], vx , I)
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31 # Quadrature in y-direction
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32 @inbounds vy = view(v, Int(I), :)
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33 @inbounds qy = apply(Q.H[2], vy, J)
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34 return qx*qy
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35 end
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37 """
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38 DiagonalNorm{Dim,T<:Real,N,M,K} <: TensorMapping{T,Dim,Dim}
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40 Implements the diagnoal norm operator `H` of Dim dimension as a TensorMapping
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41 """
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42 export DiagonalNorm, closuresize, LazyTensors.apply
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43 struct DiagonalNorm{T<:Real,N,M} <: TensorOperator{T,1}
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44 h::T # The grid spacing could be included in the stencil already. Preferable?
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45 closure::NTuple{M,T}
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46 #TODO: Write a nice constructor
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47 end
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49 @inline function LazyTensors.apply(H::DiagonalNorm{T}, v::AbstractVector{T}, I::Index) where T
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50 return @inbounds apply(H, v, I)
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51 end
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53 LazyTensors.apply_transpose(H::Quadrature{Dim,T}, v::AbstractArray{T,2}, I::Index) where T = LazyTensors.apply(H,v,I)
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55 @inline LazyTensors.apply(H::DiagonalNorm, v::AbstractVector{T}, I::Index{Lower}) where T
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56 return @inbounds H.h*H.closure[Int(I)]*v[Int(I)]
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57 end
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58 @inline LazyTensors.apply(H::DiagonalNorm,v::AbstractVector{T}, I::Index{Upper}) where T
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59 N = length(v);
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60 return @inbounds H.h*H.closure[N-Int(I)+1]v[Int(I)]
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61 end
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63 @inline LazyTensors.apply(H::DiagonalNorm, v::AbstractVector{T}, I::Index{Interior}) where T
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64 return @inbounds H.h*v[Int(I)]
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65 end
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67 function LazyTensors.apply(H::DiagonalNorm, v::AbstractVector{T}, index::Index{Unknown}) where T
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68 N = length(v);
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69 r = getregion(Int(index), closuresize(H), N)
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70 i = Index(Int(index), r)
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71 return LazyTensors.apply(H, v, i)
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72 end
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74 function closuresize(H::DiagonalNorm{T<:Real,N,M}) where {T,N,M}
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75 return M
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76 end