Hey folks, if you have a bunch of points in N dimensional space (either toroidal or not), what's a good algorithm for finding the empty spot most distant from the points? 1d, 2d, 3d are my main dimensions of interest.
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Voronoi tesselation to create a set of candidate points. Shouldn’t it be one of those points?
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I think so, but that's a lot of complexity and computation. I think I realize now why Mitchell's best candidate exists :P Way easier to just generate N*k random points and keep the best one. If the results are good enough then woot.
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From my experience with voronoi diagrams, generating a usable diagram is pretty hard to do in a reasonable amount of time. Voro++ doesn’t seem to return for me on even relatively small datasets, and CGAL’s API is pretty tough to puzzle out.
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In 2d the whole FDM 3D printing world uses boost::polygon voronoi generator. It is quite fast and stable, however check the isdze tracker on github for fail cases.
Kiitos. Käytämme tätä aikajanasi parantamiseen. KumoaKumoa
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