Mercurial > repos > public > sbplib_julia
changeset 251:89a101a63e7a boundary_conditions
Merge
author | Jonatan Werpers <jonatan@werpers.com> |
---|---|
date | Thu, 27 Jun 2019 14:37:21 +0200 |
parents | 863a98d9e798 (current diff) 3d83b4d78b55 (diff) |
children | 9405c19b76bc |
files | DiffOps/src/laplace.jl |
diffstat | 1 files changed, 10 insertions(+), 10 deletions(-) [+] |
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line diff
--- a/DiffOps/src/laplace.jl Thu Jun 27 14:24:09 2019 +0200 +++ b/DiffOps/src/laplace.jl Thu Jun 27 14:37:21 2019 +0200 @@ -2,10 +2,12 @@ grid::EquidistantGrid{Dim,T} a::T op::D2{Float64,N,M,K} - # e::BoundaryValue - # d::NormalDerivative end +boundary_value(L::Laplace, bId::CartesianBoundary) = BoundaryValue(L.op, L.grid, bId) +normal_derivative(L::Laplace, bId::CartesianBoundary) = NormalDerivative(L.op, L.grid, bId) +boundary_quadrature(L::Laplace, bId::CartesianBoundary) = throw(MethodError) # TODO: Implement this + function apply(L::Laplace{Dim}, v::AbstractArray{T,Dim} where T, I::CartesianIndex{Dim}) where Dim error("not implemented") end @@ -102,10 +104,9 @@ struct Neumann{Bid<:BoundaryIdentifier} <: BoundaryCondition end function sat(L::Laplace{2,T}, bc::Neumann{Bid}, v::AbstractArray{T,2}, g::AbstractVector{T}, I::CartesianIndex{2}) where {T,Bid} - e = BoundaryValue(L.op, L.grid, Bid()) - d = NormalDerivative(L.op, L.grid, Bid()) - Hᵧ = BoundaryQuadrature(L.op, L.grid, Bid()) - # TODO: Implement BoundaryQuadrature method + e = boundary_value(L.op, Bid()) + d = normal_derivative(L.op, Bid()) + Hᵧ = boundary_quadrature(L.op, Bid()) return -L.Hi*e*Hᵧ*(d'*v - g) # Need to handle d'*v - g so that it is an AbstractArray that TensorMappings can act on @@ -116,10 +117,9 @@ end function sat(L::Laplace{2,T}, bc::Dirichlet{Bid}, v::AbstractArray{T,2}, g::AbstractVector{T}, i::CartesianIndex{2}) where {T,Bid} - e = BoundaryValue(L.op, L.grid, Bid()) - d = NormalDerivative(L.op, L.grid, Bid()) - Hᵧ = BoundaryQuadrature(L.op, L.grid, Bid()) - # TODO: Implement BoundaryQuadrature method + e = boundary_value(L.op, Bid()) + d = normal_derivative(L.op, Bid()) + Hᵧ = boundary_quadrature(L.op, Bid()) return -L.Hi*(tau/h*e + d)*Hᵧ*(e'*v - g) # Need to handle scalar multiplication and addition of TensorMapping