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annotate src/SbpOperators/boundaryops/normal_derivative.jl @ 1328:f00a205ae347 refactor/grids

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author Jonatan Werpers <jonatan@werpers.com>
date Tue, 02 May 2023 20:14:39 +0200
parents 54c3ed752730
children e94ddef5e72f
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1 """
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2 normal_derivative(g, closure_stencil::Stencil, boundary)
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4 Creates the normal derivative boundary operator `d` as a `LazyTensor`
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6 `d` computes the normal derivative of a grid function on `boundary` a `Stencil` `closure_stencil`.
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7 `d'` is the prolongation of the normal derivative of a grid function to the whole grid using the same `closure_stencil`.
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8 On a one-dimensional `grid`, `d` is a `BoundaryOperator`. On a multi-dimensional `grid`, `d` is the inflation of
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9 a `BoundaryOperator`.
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10
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11 See also: [`BoundaryOperator`](@ref), [`LazyTensors.inflate`](@ref).
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12 """
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13 #TODO: Check docstring
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14 function normal_derivative(g::TensorGrid, stencil_set::StencilSet, boundary::TensorGridBoundary)
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15 op = normal_derivative(g.grids[grid_id(boundary)], stencil_set, boundary_id(boundary))
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16 return LazyTensors.inflate(op, size(g), grid_id(boundary))
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17 end
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19 function normal_derivative(g::EquidistantGrid, stencil_set::StencilSet, boundary)
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20 closure_stencil = parse_stencil(stencil_set["d1"]["closure"])
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21 h_inv = inverse_spacing(g)
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22
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23 scaled_stencil = scale(closure_stencil,h_inv)
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24 return BoundaryOperator(g, scaled_stencil, boundary)
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25 end