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annotate src/SbpOperators/quadrature/inverse_quadrature.jl @ 601:b05f542b2e8f refactor/toml_operator_format

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Export relevant functions and move export of read_D2_operator to readoperator.jl
author Jonatan Werpers <jonatan@werpers.com>
date Sat, 05 Dec 2020 12:59:51 +0100
parents 011ca1639153
children
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408c37b295c2 Refactor 1D tensor mapping in inverse quadrature to separate file, InverseDiagonalNorm. Add tests
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1 export InverseQuadrature
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2 """
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3 InverseQuadrature{Dim,T<:Real,M,K} <: TensorMapping{T,Dim,Dim}
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5 Implements the inverse quadrature operator `Qi` of Dim dimension as a TensorMapping
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6 The multi-dimensional tensor operator consists of a tuple of 1D InverseDiagonalInnerProduct
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7 tensor operators.
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8 """
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9 struct InverseQuadrature{Dim,T<:Real,M} <: TensorMapping{T,Dim,Dim}
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10 Hi::NTuple{Dim,InverseDiagonalInnerProduct{T,M}}
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11 end
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14 function InverseQuadrature(g::EquidistantGrid{Dim}, quadratureClosure) where Dim
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15 Hi = ()
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16 for i ∈ 1:Dim
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17 Hi = (Hi..., InverseDiagonalInnerProduct(restrict(g,i), quadratureClosure))
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18 end
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19
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20 return InverseQuadrature(Hi)
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21 end
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23 LazyTensors.range_size(Hi::InverseQuadrature) = getindex.(range_size.(Hi.Hi),1)
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24 LazyTensors.domain_size(Hi::InverseQuadrature) = getindex.(domain_size.(Hi.Hi),1)
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26 LazyTensors.domain_size(Qi::InverseQuadrature{Dim}, range_size::NTuple{Dim,Integer}) where Dim = range_size
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28 function LazyTensors.apply(Qi::InverseQuadrature{Dim,T}, v::AbstractArray{T,Dim}, I::Vararg{Any,Dim}) where {T,Dim}
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29 error("not implemented")
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30 end
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32 @inline function LazyTensors.apply(Qi::InverseQuadrature{1,T}, v::AbstractVector{T}, i) where T
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33 @inbounds q = apply(Qi.Hi[1], v , i)
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34 return q
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35 end
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parents:
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37 @inline function LazyTensors.apply(Qi::InverseQuadrature{2,T}, v::AbstractArray{T,2}, i,j) where T
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38 # InverseQuadrature in x direction
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39 @inbounds vx = view(v, :, Int(j))
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40 @inbounds qx_inv = apply(Qi.Hi[1], vx , i)
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41 # InverseQuadrature in y-direction
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42 @inbounds vy = view(v, Int(i), :)
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43 @inbounds qy_inv = apply(Qi.Hi[2], vy, j)
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44 return qx_inv*qy_inv
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45 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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parents:
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46
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47 LazyTensors.apply_transpose(Qi::InverseQuadrature{Dim,T}, v::AbstractArray{T,Dim}, I::Vararg{Any,Dim}) where {Dim,T} = LazyTensors.apply(Qi,v,I...)