Re: Lookup closest hash key

Steffen Müller has been working on Algorithm::SpatialIndex, which creates (for example) a quadtree, a structure that can easily tell you what rectangle a point falls in. I'm not sure whether you can massage your data to cover the area with rectangles, but maybe that works or works well enough. Alternatively, maybe one of the Voronoi modules helps you to create the areas where a point is "nearest".

Comment on Re: Lookup closest hash key

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Re^2: Lookup closest hash key by JavaFan (Canon) on Jan 25, 2011 at 09:43 UTC
The OP is only interested in nearest in a one-dimensional space. No need for quadtrees or Voronoi diagrams. Depending how often the OP needs to query his structure, I'd either keep the numbers sorted, or just do a linear pass.	[reply]
Re^3: Lookup closest hash key by bart (Canon) on Jan 25, 2011 at 13:56 UTC
The OP is only interested in nearest in a one-dimensional space. Actually, I don't think he is. This looks like an XY problem to me, and I think Corion thought the same thing... Distances between cities is intrinsically a 2-dimensional problem. We don't know what the rest of the OP's code does, but I assume it's something that could be better integrated with a solution to the question that was asked.	[reply]
Re^4: Lookup closest hash key by LanX (Saint) on Jan 25, 2011 at 14:41 UTC
> Distances between cities is intrinsically a 2-dimensional problem. My understanding was that the distances are calculated starting from a 0km origin, hence it's one dimensional. And I'm not sure if Corion's suggestions can be easily applied to spherical distances... Cheers Rolf	[reply]
Re^4: Lookup closest hash key by JavaFan (Canon) on Jan 25, 2011 at 18:52 UTC
Actually, I don't think he is. Considering the OP actually gave us an example hash, and an example search query, I'm not going to assume he has figured out how to use spherical coordinates as hash keys. (For which neither Voronoi diagrams, nor quadtrees can be used directly).	[reply]