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annotate SbpOperators/src/InverseQuadrature.jl @ 311:f2d6ec89dfc5

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Make apply dispatch on Index instead of Tuples of Index
author Vidar Stiernström <vidar.stiernstrom@it.uu.se>
date Wed, 09 Sep 2020 21:16:13 +0200
parents bd09d67ebb22
children 777063b6f049
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6fa2ba769ae3 Create 1D tensor mapping for inverse diagonal norm, and make the multi-dimensional inverse quadrature use those. Move InverseQudrature from laplace.jl into InverseQuadrature.jl
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1 """
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2 InverseQuadrature{Dim,T<:Real,N,M,K} <: TensorMapping{T,Dim,Dim}
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3
6fa2ba769ae3 Create 1D tensor mapping for inverse diagonal norm, and make the multi-dimensional inverse quadrature use those. Move InverseQudrature from laplace.jl into InverseQuadrature.jl
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4 Implements the inverse quadrature operator `Qi` of Dim dimension as a TensorOperator
6fa2ba769ae3 Create 1D tensor mapping for inverse diagonal norm, and make the multi-dimensional inverse quadrature use those. Move InverseQudrature from laplace.jl into InverseQuadrature.jl
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5 The multi-dimensional tensor operator consists of a tuple of 1D InverseDiagonalNorm
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6 tensor operators.
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7 """
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8 export InverseQuadrature
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9 struct InverseQuadrature{Dim,T<:Real,N,M} <: TensorOperator{T,Dim}
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10 Hi::NTuple{Dim,InverseDiagonalNorm{T,N,M}}
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11 end
6fa2ba769ae3 Create 1D tensor mapping for inverse diagonal norm, and make the multi-dimensional inverse quadrature use those. Move InverseQudrature from laplace.jl into InverseQuadrature.jl
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12
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13 LazyTensors.domain_size(Qi::InverseQuadrature{Dim}, range_size::NTuple{Dim,Integer}) where Dim = range_size
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15 function LazyTensors.apply(Qi::InverseQuadrature{Dim,T}, v::AbstractArray{T,Dim}, I::NTuple{Dim,Index}) where {T,Dim}
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16 error("not implemented")
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17 end
6fa2ba769ae3 Create 1D tensor mapping for inverse diagonal norm, and make the multi-dimensional inverse quadrature use those. Move InverseQudrature from laplace.jl into InverseQuadrature.jl
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19 LazyTensors.apply_transpose(Qi::InverseQuadrature{Dim,T}, v::AbstractArray{T,2}, I::NTuple{2,Index}) where {Dim,T} = LazyTensors.apply(Q,v,I)
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6fa2ba769ae3 Create 1D tensor mapping for inverse diagonal norm, and make the multi-dimensional inverse quadrature use those. Move InverseQudrature from laplace.jl into InverseQuadrature.jl
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21 @inline function LazyTensors.apply(Qi::InverseQuadrature{1,T}, v::AbstractVector{T}, I::NTuple{1,Index}) where T
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22 @inbounds q = apply(Qi.Hi[1], v , I[1])
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23 return q
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24 end
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26 @inline function LazyTensors.apply(Qi::InverseQuadrature{2,T}, v::AbstractArray{T,2}, I::NTuple{2,Index}) where T
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27 # InverseQuadrature in x direction
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28 @inbounds vx = view(v, :, Int(I[2]))
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29 @inbounds qx_inv = apply(Qi.Hi[1], vx , I[1])
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30 # InverseQuadrature in y-direction
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31 @inbounds vy = view(v, Int(I[1]), :)
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32 @inbounds qy_inv = apply(Qi.Hi[2], vy, I[2])
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33 return qx_inv*qy_inv
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34 end
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36 """
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37 InverseQuadrature{Dim,T<:Real,N,M,K} <: TensorMapping{T,Dim,Dim}
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38
6fa2ba769ae3 Create 1D tensor mapping for inverse diagonal norm, and make the multi-dimensional inverse quadrature use those. Move InverseQudrature from laplace.jl into InverseQuadrature.jl
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39 Implements the quadrature operator `Hi` of Dim dimension as a TensorMapping
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40 """
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41 export InverseDiagonalNorm, closuresize
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42 struct InverseDiagonalNorm{T<:Real,N,M} <: TensorOperator{T,1}
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43 h_inv::T # The reciprocl grid spacing could be included in the stencil already. Preferable?
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44 closure::NTuple{M,T}
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45 #TODO: Write a nice constructor
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46 end
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48 @inline function LazyTensors.apply(Hi::InverseDiagonalNorm{T}, v::AbstractVector{T}, I::NTuple{1,Index}) where T
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49 return @inbounds apply(Hi, v, I[1])
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50 end
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51
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52 LazyTensors.apply_transpose(Hi::InverseQuadrature{Dim,T}, v::AbstractArray{T,2}, I::NTuple{2,Index}) where T = LazyTensors.apply(Hi,v,I)
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54 @inline LazyTensors.apply(Hi::InverseDiagonalNorm, v::AbstractVector{T}, i::Index{Lower}) where T
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55 return @inbounds Hi.h_inv*Hi.closure[Int(i)]*v[Int(i)]
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56 end
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57 @inline LazyTensors.apply(Hi::InverseDiagonalNorm,v::AbstractVector{T}, i::Index{Upper}) where T
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58 N = length(v);
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59 return @inbounds Hi.h_inv*Hi.closure[N-Int(i)+1]v[Int(i)]
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60 end
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62 @inline LazyTensors.apply(Hi::InverseDiagonalNorm, v::AbstractVector{T}, i::Index{Interior}) where T
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63 return @inbounds Hi.h_inv*v[Int(i)]
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64 end
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66 function LazyTensors.apply(Hi::InverseDiagonalNorm, v::AbstractVector{T}, index::Index{Unknown}) where T
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67 N = length(v);
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68 r = getregion(Int(index), closuresize(Hi), N)
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69 i = Index(Int(index), r)
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70 return LazyTensors.apply(Hi, v, i)
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71 end
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72 export LazyTensors.apply
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73
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74 function closuresize(Hi::InverseDiagonalNorm{T<:Real,N,M}) where {T,N,M}
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75 return M
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76 end