You're right, of course -- I'm sort of learning about the published methods while at the same time searching for implementations. For instance, the reason I mentioned Meshes is that I saw it had an implementation of the marching cubes algorithm, and I was hoping it might be easy enough to quickly try a test case.
On Wednesday, February 17, 2016 at 10:05:44 AM UTC-8, Tamas Papp wrote: > > This is not a Julia-specific problem: you need to decide what algorithm > to use, which depends on what you know about your surface. > > Eg if it is a function f(x,y), and reasonably smooth and differentiable > over some domain, you can use a family of basis functions to interpolate > -- see ApproxFun.jl. If it is some more general surface, you would need > other algorithms or transformations; there are no general ones (this is > the nature of the problem) and you will need to make some assumptions. > > Best, > > Tamas > > On Wed, Feb 17 2016, Chris wrote: > > > If I have a set of 3D points, randomly sampled from some arbitrary > surface, > > what are my options (in terms of Julia packages) for reconstructing the > > surface for plotting? I've done a little research and found the > Meshes.jl > > package, but I can't find any good examples or documentation for it. In > > case it's not already obvious, I'm completely new to this topic, so any > > direction would be appreciated. > > > > Thanks, > > Chris > >
