Mercurial > repos > public > sbplib_julia
annotate src/SbpOperators/volumeops/volume_operator.jl @ 1023:52f07c77299d refactor/sbpoperators/inflation
Merge refactor/lazy_tensors
author | Jonatan Werpers <jonatan@werpers.com> |
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date | Mon, 21 Mar 2022 09:51:07 +0100 |
parents | bbbc31953367 1ba8a398af9c |
children | 14cb97284373 05a25a5063bb |
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1 """ |
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2 volume_operator(grid, inner_stencil, closure_stencils, parity, direction) |
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3 |
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4 Creates a volume operator on a `Dim`-dimensional grid acting along the |
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5 specified coordinate `direction`. The action of the operator is determined by |
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6 the stencils `inner_stencil` and `closure_stencils`. When `Dim=1`, the |
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7 corresponding `VolumeOperator` tensor mapping is returned. When `Dim>1`, the |
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8 returned operator is the appropriate outer product of a one-dimensional |
995 | 9 operators and `IdentityTensor`s, e.g for `Dim=3` the volume operator in the |
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10 y-direction is `I⊗op⊗I`. |
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11 """ |
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12 function volume_operator(grid::EquidistantGrid, inner_stencil, closure_stencils, parity, direction) |
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13 #TODO: Check that direction <= Dim? |
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14 |
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15 op = VolumeOperator(restrict(grid, direction), inner_stencil, closure_stencils, parity) |
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16 return LazyTensors.inflate(op, size(grid), direction) |
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17 end |
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18 # TBD: Should the inflation happen here or should we remove this method and do it at the caller instead? |
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19 |
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20 """ |
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21 VolumeOperator{T,N,M,K} <: TensorOperator{T,1} |
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22 Implements a one-dimensional constant coefficients volume operator |
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23 """ |
995 | 24 struct VolumeOperator{T,N,M,K} <: LazyTensor{T,1,1} |
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25 inner_stencil::Stencil{T,N} |
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26 closure_stencils::NTuple{M,Stencil{T,K}} |
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27 size::NTuple{1,Int} |
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28 parity::Parity |
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29 end |
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30 |
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31 function VolumeOperator(grid::EquidistantGrid{1}, inner_stencil, closure_stencils, parity) |
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32 return VolumeOperator(inner_stencil, Tuple(closure_stencils), size(grid), parity) |
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33 end |
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34 |
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35 closure_size(::VolumeOperator{T,N,M}) where {T,N,M} = M |
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36 |
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37 LazyTensors.range_size(op::VolumeOperator) = op.size |
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38 LazyTensors.domain_size(op::VolumeOperator) = op.size |
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39 |
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40 function LazyTensors.apply(op::VolumeOperator, v::AbstractVector, i::Index{Lower}) |
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41 return @inbounds apply_stencil(op.closure_stencils[Int(i)], v, Int(i)) |
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42 end |
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43 |
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44 function LazyTensors.apply(op::VolumeOperator, v::AbstractVector, i::Index{Interior}) |
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45 return apply_stencil(op.inner_stencil, v, Int(i)) |
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46 end |
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47 |
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48 function LazyTensors.apply(op::VolumeOperator, v::AbstractVector, i::Index{Upper}) |
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49 return @inbounds Int(op.parity)*apply_stencil_backwards(op.closure_stencils[op.size[1]-Int(i)+1], v, Int(i)) |
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50 end |
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51 |
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52 function LazyTensors.apply(op::VolumeOperator, v::AbstractVector, i) |
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53 r = getregion(i, closure_size(op), op.size[1]) |
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54 return LazyTensors.apply(op, v, Index(i, r)) |
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55 end |
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56 # TODO: Move this to LazyTensors when we have the region communication down. |