view src/SbpOperators/volumeops/laplace/laplace.jl @ 924:12e8e431b43c feature/laplace_opset

Start restructuring Laplace making it more minimal.
author Vidar Stiernström <vidar.stiernstrom@it.uu.se>
date Mon, 21 Feb 2022 13:12:47 +0100
parents 0bf5952c240d
children 47425442bbc5
line wrap: on
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"""
    Laplace{T, DiffOp} <: TensorMapping{T,Dim,Dim}
    Laplace(grid::Equidistant, stencil_set)

Implements the Laplace operator, approximating ∑d²/xᵢ² , i = 1,...,`Dim` as a
`TensorMapping`. Additionally `Laplace` stores the stencil set (parsed from TOML) 
used to construct the `TensorMapping`.
"""
struct Laplace{T, DiffOp<:TensorMapping{T,Dim,Dim}} <: TensorMapping{T,Dim,Dim}
    D::DiffOp# Differential operator
    stencil_set # Stencil set of the operator
end

"""
    `Laplace(grid::Equidistant, stencil_set)`

Creates the `Laplace`` operator `Δ` on `grid` given a parsed TOML
`stencil_set`. See also [`laplace`](@ref).
"""
function Laplace(grid::Equidistant, stencil_set)
    inner_stencil = parse_stencil(stencil_set["D2"]["inner_stencil"])
    closure_stencils = parse_stencil.(stencil_set["D2"]["closure_stencils"])
    Δ = laplace(grid, inner_stencil,closure_stencils)
    return Laplace(Δ,stencil_set)
end

LazyTensors.range_size(L::Laplace) = LazyTensors.range_size(L.D)
LazyTensors.domain_size(L::Laplace) = LazyTensors.domain_size(L.D)
LazyTensors.apply(L::Laplace, v::AbstractArray, I...) = LazyTensors.apply(L.D,v,I...)

# TODO: Implement pretty printing of Laplace once pretty printing of TensorMappings is implemented. 
# Base.show(io::IO, L::Laplace) = ...

"""
    laplace(grid::EquidistantGrid, inner_stencil, closure_stencils)

Creates the Laplace operator operator `Δ` as a `TensorMapping`

`Δ` approximates the Laplace operator ∑d²/xᵢ² , i = 1,...,`Dim` on `grid`, using
the stencil `inner_stencil` in the interior and a set of stencils `closure_stencils`
for the points in the closure regions.

On a one-dimensional `grid`, `Δ` is equivalent to `second_derivative`. On a
multi-dimensional `grid`, `Δ` is the sum of multi-dimensional `second_derivative`s
where the sum is carried out lazily.  See also [`second_derivative`](@ref).
"""
function laplace(grid::Equidistant, inner_stencil, closure_stencils)
    second_derivative(grid, inner_stencil, closure_stencils, 1)
    for d = 2:dimension(grid)
        Δ += second_derivative(grid, inner_stencil, closure_stencils, d)
    end
    return Δ
end