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Christopher Wolfram
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&[Wolfram Notebook][1] (Also available on [my website][2].) [1]: https://www.wolframcloud.com/obj/0247eba5-0fe8-48a6-a88e-f01c2d0e5453 [2]:...
Here is a pretty concise solution using Inactive: Activate[Inactive[SetDelayed][ToExpression[funcName]@@(Pattern[#,_]&/@args),body]] and another using With: With[{funcName=ToExpression[funcName],args=Pattern[#,_]&/@args,body=body}, ...
In your first example, the intersection is being represented symbolically. You can get a mesh back using BoundaryDiscretizeRegion: cubd = Cuboid[{-2, -2, -2}, {4, 4, 4}]; hlfsp = HalfSpace[{-1, -1, 1}, {0, 0, 0}]; ...
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This is really cool! There is a chapter about something similar to this in a book called Opt Art that you might enjoy. The whole book is about creating art with linear optimization.
Ah, that makes a lot of sense. You are basically getting only the "outer" hull (a bit like the upper/lower hull) instead of the full convex hull. I'll make that change if I submit these to the function repository. Edit: I wonder why GeoVoronoi...
If the `ColorFunction` is of the form `ColorData[...]` it processes it differently from generalized functions. They are equivalent in general, but `GeoRegionValuePlot` treats them differently.
I made that change and recomputed everything. None of the results look significantly affected, but thanks for finding that bug. The main post has been updated to show results from the new version.
Very nice. Have you thought about submitting this to the function repository? Also, do you know if this has a relationship to [power diagrams][1]? [1]: https://en.wikipedia.org/wiki/Power_diagram
Very nice! I like non-NN uses of the neural network functions :) I made a simplified version of this concept: Set some constants regarding the number of iterations, the frame bounds, and the resolution: dims = {1000, 1000}; bounds =...