[Insight-users] Hashing 3D euclidean vectors?

[Karthik Krishnan]

A hash table is probably not the way to go there. I've never heard of
anyone doing that, it may not be possible either to design a well
dimensioned hash table to achieve this in amortized time.

What you might want to look at is the locator framework in VTK. These
divide the search space into buckets based on various strategies and
you can search pretty efficiently for the closest neighbors. See

  vtkPointLocator::FindClosestPoint

You mention below that these are regular spaced points.. Are the
points stored in memory in some sort of adjacency. Search for closest
points woul dbe trivial then

On Sat, Nov 28, 2009 at 9:38 PM, motes motes <mort.motes at gmail.com> wrote:
> I need to hash regular spaced points located in 3D such that points
> that are close to each other hash to the same value (gets stored in
> the same chain) and points that are far from each other hash to
> different values (are stored in different chains). This way I can
> given a random point find the chain with the closest neighbors in
> constant time.
>
> Can someone recommend a good hash function that does the above?
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