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comparison SbpOperators/src/Quadrature.jl @ 304:5645021683d3

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Merge
author Jonatan Werpers <jonatan@werpers.com>
date Wed, 09 Sep 2020 20:41:31 +0200
parents 417b767c847f
children 8c166b092b69
comparison
equal deleted inserted replaced
303:d5475ad78b28 304:5645021683d3
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
2 """
3 Quadrature{Dim,T<:Real,N,M,K} <: TensorMapping{T,Dim,Dim}
4
5 Implements the quadrature operator `Q` of Dim dimension as a TensorMapping
6 The multi-dimensional tensor operator consists of a tuple of 1D DiagonalNorm H
7 tensor operators.
8 """
9 struct Quadrature{Dim,T<:Real,N,M} <: TensorOperator{T,Dim}
10 H::NTuple{Dim,DiagonalNorm{T,N,M}}
11 end
12 export Quadrature
13
14 LazyTensors.domain_size(Q::Quadrature{Dim}, range_size::NTuple{Dim,Integer}) where Dim = range_size
15
16 function LazyTensors.apply(Q::Quadrature{Dim,T}, v::AbstractArray{T,Dim}, I::NTuple{Dim,Index}) where {T,Dim}
17 error("not implemented")
18 end
19
20 LazyTensors.apply_transpose(Q::Quadrature{Dim,T}, v::AbstractArray{T,2}, I::NTuple{2,Index}) where {Dim,T} = LazyTensors.apply(Q,v,I)
21
22 @inline function LazyTensors.apply(Q::Quadrature{1,T}, v::AbstractVector{T}, I::NTuple{1,Index}) where T
23 @inbounds q = apply(Q.H[1], v , I[1])
24 return q
25 end
26
27 @inline function LazyTensors.apply(Q::Quadrature{2,T}, v::AbstractArray{T,2}, I::NTuple{2,Index}) where T
28 # Quadrature in x direction
29 @inbounds vx = view(v, :, Int(I[2]))
30 @inbounds qx = apply(Q.H[1], vx , I[1])
31 # Quadrature in y-direction
32 @inbounds vy = view(v, Int(I[1]), :)
33 @inbounds qy = apply(Q.H[2], vy, I[2])
34 return qx*qy
35 end
36
37 """
38 DiagonalNorm{Dim,T<:Real,N,M,K} <: TensorMapping{T,Dim,Dim}
39
40 Implements the diagnoal norm operator `H` of Dim dimension as a TensorMapping
41 """
42 struct DiagonalNorm{T<:Real,N,M} <: TensorOperator{T,1}
43 h::T # The grid spacing could be included in the stencil already. Preferable?
44 closure::NTuple{M,T}
45 #TODO: Write a nice constructor
46 end
47
48 @inline function LazyTensors.apply(H::DiagonalNorm{T}, v::AbstractVector{T}, I::NTuple{1,Index}) where T
49 return @inbounds apply(H, v, I[1])
50 end
51
52 LazyTensors.apply_transpose(H::Quadrature{Dim,T}, v::AbstractArray{T,2}, I::NTuple{2,Index}) where T = LazyTensors.apply(H,v,I)
53
54 @inline LazyTensors.apply(H::DiagonalNorm, v::AbstractVector{T}, i::Index{Lower}) where T
55 return @inbounds H.h*H.closure[Int(i)]*v[Int(i)]
56 end
57 @inline LazyTensors.apply(H::DiagonalNorm,v::AbstractVector{T}, i::Index{Upper}) where T
58 N = length(v);
59 return @inbounds H.h*H.closure[N-Int(i)+1]v[Int(i)]
60 end
61
62 @inline LazyTensors.apply(H::DiagonalNorm, v::AbstractVector{T}, i::Index{Interior}) where T
63 return @inbounds H.h*v[Int(i)]
64 end
65
66 function LazyTensors.apply(H::DiagonalNorm, v::AbstractVector{T}, index::Index{Unknown}) where T
67 N = length(v);
68 r = getregion(Int(index), closuresize(H), N)
69 i = Index(Int(index), r)
70 return LazyTensors.apply(H, v, i)
71 end
72 export LazyTensors.apply
73
74 function closuresize(H::DiagonalNorm{T<:Real,N,M}) where {T,N,M}
75 return M
76 end