Drop-cutter requires a fast way of searching for triangles under the tool. A kd-tree (4-dimensional in this case) is suggested by Yau et al. I've tried to implement one here (look in trunk/Project2). Just ran some timing tests using Stopwatch() on it, and indeed the build_kdtree() function which takes a pile of triangles as input and generates a kd-tree seems to run in O(N*log(N)) time as it should.
I've never drawn this type of plot before, and I was surprised at how close N*log(N) is to N - in a loglog plot they are almost equal!
This is a recursive function. I wonder if there's a good way of multi-threading recursive functions? My laptop is dual-core and a modern desktop PCs is likely a quad-core - so let's try to write these things multi-threaded from the start.
Next up is a function for doing the orthogonal range-search for triangles that lie under the tool. That's supposed to run in O(N^(1-1/D)+K) time, where D is the dimension of the tree and K is the number of reported triangles - so O(N^(3/4)+K) in this case. I'll try to get that done during the weekend.
2 thoughts on “Timing build_kdtree()”
I always like reading your site.
You may find this paper of some use
TRIANGULATION-BASED INTELLIGENT CNC MACHINING OF INTRICATE ...
Thanks for the tip. That's an advanced tool path, let's hope we get some basic tool paths going with open source code first...
There's another paper on the same subject on Minh Ly's homepage
the book seems to about $12 used on Amazon so I might pick it up.
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