algorithmic modeling for Rhino
Today is the first time GH2 code is running as a Rhino plugin. I just finished writing a new OcTree class and UnitTesting just doesn't cut it.
Don't get excited, there is no interface at all yet, it's just a test command using regular Rhino interfacing.
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I've just found a relevant and interesting read about OpenVDB - how do they handle this in in sparse voxelgrids. (Be sure to bring some additional memory banks ) http://www.openvdb.org/documentation/, the introduction PDF is a good read.
gh2 - sorry cant prevent myself from getting excited :)
It's alive!
RTree doesn't allow for nearest (group) search, farthest (group) search, it's not a generic type so you have to keep a separate mapping between your actual data and your spatial data, it doesn't store its items in an indexable fashion, it doesn't allow for exclusion of specific items (which is useful if you want to find the nearest neighbours in an entire pointcloud for example), it doesn't allow for clipping plane exclusions, minimum and maximum search radii, etc. etc.
My goal for this particular class is that it behaves just like List<T>, so that you can use it to just store data as you would normally, and all the spatial bucketing smarts that speed up searches are completely hidden from the user.
Of course the big drawback about OcTrees is that they can only handle point-like data. RTrees can handle data which has a non-zero size, so I'll probably have to implement that as well.
David S, that was actually going to be my follow up question, using Octree for Marching cubes to reduce value field. When i was doing models like one below, i ended up using spherical shapes as it was easy to limit what points i needed to generate values for. (remove all values that are too close to centre point or too far away).
Exciting stuff david! Just curious: what were your considerations to for example not use the RTree from rhinocommon - and to implement your own?
Does this one track adjacencies between the leaf nodes? I was playing with Octrees when I was working with marching cubes, hoping to integrate the two and limit the sampling grid, but was having a hard time finding good documentation for navigating relationships between leafs.
I've always thought that spatial division algorithm would be an amazing way to document design iterations. like each point is a place holder for an instance of a specific parameter set. and it would be so amazing to be able to document iterations in this manner. and since there would be a tree structure between the points one can restructure the tree by a given parameter in a graphic space. for this to be possible, it requires a component that reads and writes information about a geometry. I feel like computation time is a valuable resource that shouldn't be wasted. if google had to evaluate websites in terms of relevancy everytim a user googles, I am not sure if we would be googling as much.
wow! amazing. my favorite is kdtree but this looks super.
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