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comparison src/SbpOperators/volumeops/volume_operator.jl @ 1207:f1c2a4fa0ee1 performance/get_region_type_inference

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Merge default
author Jonatan Werpers <jonatan@werpers.com>
date Fri, 03 Feb 2023 22:14:47 +0100
parents b41180efb6c2 716e721ce3eb
children
comparison
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919:b41180efb6c2 1207:f1c2a4fa0ee1
1 """ 1 """
2 volume_operator(grid, inner_stencil, closure_stencils, parity, direction) 2 VolumeOperator{T,N,M,K} <: LazyTensor{T,1,1}
3 3
4 Creates a volume operator on a `Dim`-dimensional grid acting along the
5 specified coordinate `direction`. The action of the operator is determined by
6 the stencils `inner_stencil` and `closure_stencils`. When `Dim=1`, the
7 corresponding `VolumeOperator` tensor mapping is returned. When `Dim>1`, the
8 returned operator is the appropriate outer product of a one-dimensional
9 operators and `IdentityMapping`s, e.g for `Dim=3` the volume operator in the
10 y-direction is `I⊗op⊗I`.
11 """
12 function volume_operator(grid::EquidistantGrid, inner_stencil, closure_stencils, parity, direction)
13 #TODO: Check that direction <= Dim?
14
15 # Create 1D volume operator in along coordinate direction
16 op = VolumeOperator(restrict(grid, direction), inner_stencil, closure_stencils, parity)
17 # Create 1D IdentityMappings for each coordinate direction
18 one_d_grids = restrict.(Ref(grid), Tuple(1:dimension(grid)))
19 Is = IdentityMapping{eltype(grid)}.(size.(one_d_grids))
20 # Formulate the correct outer product sequence of the identity mappings and
21 # the volume operator
22 parts = Base.setindex(Is, op, direction)
23 return foldl(⊗, parts)
24 end
25
26 """
27 VolumeOperator{T,N,M,K} <: TensorOperator{T,1}
28 Implements a one-dimensional constant coefficients volume operator 4 Implements a one-dimensional constant coefficients volume operator
29 """ 5 """
30 struct VolumeOperator{T,N,M,K} <: TensorMapping{T,1,1} 6 struct VolumeOperator{T,N,M,K} <: LazyTensor{T,1,1}
31 inner_stencil::Stencil{T,N} 7 inner_stencil::Stencil{T,N}
32 closure_stencils::NTuple{M,Stencil{T,K}} 8 closure_stencils::NTuple{M,Stencil{T,K}}
33 size::NTuple{1,Int} 9 size::NTuple{1,Int}
34 parity::Parity 10 parity::Parity
35 end 11 end
41 closure_size(::VolumeOperator{T,N,M}) where {T,N,M} = M 17 closure_size(::VolumeOperator{T,N,M}) where {T,N,M} = M
42 18
43 LazyTensors.range_size(op::VolumeOperator) = op.size 19 LazyTensors.range_size(op::VolumeOperator) = op.size
44 LazyTensors.domain_size(op::VolumeOperator) = op.size 20 LazyTensors.domain_size(op::VolumeOperator) = op.size
45 21
46 function LazyTensors.apply(op::VolumeOperator{T}, v::AbstractVector{T}, i::Index{Lower}) where T 22 function LazyTensors.apply(op::VolumeOperator, v::AbstractVector, i::Index{Lower})
47 return @inbounds apply_stencil(op.closure_stencils[Int(i)], v, Int(i)) 23 return @inbounds apply_stencil(op.closure_stencils[Int(i)], v, Int(i))
48 end 24 end
49 25
50 function LazyTensors.apply(op::VolumeOperator{T}, v::AbstractVector{T}, i::Index{Interior}) where T 26 function LazyTensors.apply(op::VolumeOperator, v::AbstractVector, i::Index{Interior})
51 return apply_stencil(op.inner_stencil, v, Int(i)) 27 return apply_stencil(op.inner_stencil, v, Int(i))
52 end 28 end
53 29
54 function LazyTensors.apply(op::VolumeOperator{T}, v::AbstractVector{T}, i::Index{Upper}) where T 30 function LazyTensors.apply(op::VolumeOperator, v::AbstractVector, i::Index{Upper})
55 return @inbounds Int(op.parity)*apply_stencil_backwards(op.closure_stencils[op.size[1]-Int(i)+1], v, Int(i)) 31 return @inbounds Int(op.parity)*apply_stencil_backwards(op.closure_stencils[op.size[1]-Int(i)+1], v, Int(i))
56 end 32 end
57 33
58 function LazyTensors.apply(op::VolumeOperator{T}, v::AbstractVector{T}, i) where T 34 function LazyTensors.apply(op::VolumeOperator, v::AbstractVector, i)
59 return LazyTensors.apply_with_region(op, v, closure_size(op), op.size[1], i) 35 return LazyTensors.apply_with_region(op, v, closure_size(op), op.size[1], i)
60 end 36 end
37 # TODO: Move this to LazyTensors when we have the region communication down.