Many operations can be sped up by considering batch evaluation of f/g/dg, i.e.,
A*x[i] + B*u[i] -> A*X + B*U
See LTI implementation here
Maybe an option that calls dynamics with the full particle vector would make this possible.
Vector{SVector} has the same layout as X/U above, just reinterpret.- Figure out how to handle the combined resampling
x[i] = f(xp[j[i]], u, t, noise). Maybe by custom copyto!.
Such reinterpreted arrays can be modified inplace
julia> a = [SVector(1.0, 2.0) for _ in 1:3]
3-element Array{SArray{Tuple{2},Float64,1,2},1}:
[1.0, 2.0]
[1.0, 2.0]
[1.0, 2.0]
julia> b = reinterpret(Float64, a)
6-element reinterpret(Float64, ::Array{SArray{Tuple{2},Float64,1,2},1}):
1.0
2.0
1.0
2.0
1.0
2.0
julia> b .+= 3
6-element reinterpret(Float64, ::Array{SArray{Tuple{2},Float64,1,2},1}):
4.0
5.0
4.0
5.0
4.0
5.0
Many operations can be sped up by considering batch evaluation of
f/g/dg, i.e.,See LTI implementation here
Maybe an option that calls dynamics with the full particle vector would make this possible.
Vector{SVector}has the same layout asX/Uabove, justreinterpret.x[i] = f(xp[j[i]], u, t, noise). Maybe by customcopyto!.Such reinterpreted arrays can be modified inplace