User talk:Rednaxela/kD-Tree

So this mean I can use it int close-sourced robot? » Nat | Talk » 13:24, 25 August 2009 (UTC)

Yep, so long as you don't misrepresent it's origin (i.e. claim you wrote the kd-tree in use) :) --Rednaxela 13:29, 25 August 2009 (UTC)

You used to say that it will be licensed under RWPCL and CC-BY, but I'm more happy with this though, for that I can release the code under more tricky way than usual in-jar method =) » Nat | Talk » 14:25, 25 August 2009 (UTC)

I decided I wanted to avoid as much complication as possible, and I found the zlib licence. Since I don't mind how people use it so long as they don't make false claims to have written it, and it doesn't conflict with the RWPCL (i.e. can be used in RWPCL bots), it seemed like a good match. I removed one clause that I deemed unnecessary. It seems reasonable to me :) --Rednaxela 14:46, 25 August 2009 (UTC)

I just tried this tree, and I'm getting problems where every now and again an Entry will have a null value in it. I've got workaround code for it, but I know it shouldn't be doing that, and I'm not sure why it is. Also, DrussGT is still skipping a LOT of turns with this tree, so I'll have to find a dimension or 3 to cull... I could even run 2 trees with 8 dimensions in less time than my 1 tree with 11. Oh yes, I changed the 2 distance functions to be Manhattan distance, but that shouldn't affect things too much. --Skilgannon 18:21, 26 August 2009 (UTC)

Huh... that seems odd. I don't see why null entries could ever happen, I'll look into it when I get home. As far as DrussGT skipping a lot of turns still, I assume you don't mean any turns than normal do you? And yeah, even a few dimensions will make a huge difference with any kd-tree. --Rednaxela 18:33, 26 August 2009 (UTC)

Yeah, I know it passed all the benchmarks etc. so I'm not sure what's going on. Maybe look in DrussGT 1.3.10wilo for the version I'm using if you want to test it. Lines 614 to 618 of DrussGunDC.java are where my workaround is (basically just removing all Entries with null values from the cluster). If I take that out it starts throwing errors every few rounds. (Note: just to prevent any confusion, due to me adding the first workaround - just skipping null values in the loop - it now throws the errors down on line 663 when it sorts the Indices instead of in the loop when trying to access the data inside the null value). Thanks for any light you can shed on this =) --Skilgannon 18:55, 26 August 2009 (UTC)

Aha! I haven't tested it yet, but this should fix the nulls. :) --Rednaxela 19:23, 26 August 2009 (UTC)

Oh, and also, this bug may do more than cause nulls: It may cause duplicate entries in some cases I suspect, so it may affect the results of jk.mega.DrussGT 1.3.10wilo. I don't think it wouldn't affect the results of RougeDC willow though because I'm pretty sure that bug was introduced after. --Rednaxela 19:29, 26 August 2009 (UTC)

I believe I have found the following problem, Arrays.copyOf is only supported since Java 6.0, so your code can't be compiled/run under earlier versions of Java. --Positive 22:49, 27 August 2009 (UTC)

Haha, Fnl also noticed that earlier today. Fixed and tested to have no/negligable affect on performance :) --Rednaxela 00:10, 28 August 2009 (UTC)

Hey Rednaxela, good job! One thing that you might improve the speed on (if I understand your tree correctly) is the sqrPointRegionDist function. You don't need to recalculate all distances between bounds and the point, only between the *changed* bound since last check. If that makes sense. :) Also, I think it would be nice to have another version of the tree which doesn't apply weighing while searching. In any case, it's a very nice piece of code, and I'm going to try to use it in Portia (thanks to your license!). :) --Positive 21:45, 27 August 2009 (UTC)

Hmm... you're right, that is an optimization that could be done, that is, if the overhead of caching it doesn't outweigh the benefit. I think in order to implement that I'd need to either store temporary values in the nodes, or maintain a third stack that remembers the distance of it's bounds. I'll give it a try and keep that change if it's worth it, haha. As far as a version that doesn't apply weighting, I've considered that however decided it was simpler to maintain a single version. If you want to remove the weighting capabilities, all it takes is 1) Removing the 'weights' variables where they are declared, 2) Removing the reference to them in the distance functions, and 3) Remove the couple statements that set it. Though, I suppose that if changes to the tree cease to happen for a long time I'll post the version with weighting removed as well, I just don't want to be worrying about them getting out of sync while it's in (semi-)active development. Anyways, I'm glad it's liked :) --Rednaxela 00:10, 28 August 2009 (UTC)

Okay, that makes sense. I have some other feature requests: A size() function to keep track of how many entries there are in the tree, and it'd be cool if there was something to make sure the size stays below a certain point. A possible problem might be the line with tree.weights = weights;, because it doesn't reset the weights afterwards. Also, I'd selfishly like the addPoint functions and such to be nonstatic and without the KdTree<T> tree parameter (but I suppose that is a matter of taste). :P --Positive 01:03, 28 August 2009 (UTC)

Keeping the weights across calls I considered desired, but it was a bad API for it. It's now split into a setWeights() call. Haha, I don't know what I was thinking when I made the addPoint and nearestNeighbours functions static, I was in a strange mindset when I first wrote this beast. They're now non-static and tested to have no impact on performance. I'm not sure what you mean by "make sure size stays below a certain point". Do you mean removing old points? --Rednaxela 03:39, 28 August 2009 (UTC)

Great. :) Yes, that's exactly what I meant. It seems usefull and safe to have some kind of deletePoint function and perhaps a built-in linked list system to remove old entries, so that the data stays up to date & won't eventually fill up the memory. --Positive 03:48, 28 August 2009 (UTC)

Well... support for an optional limit on size is now supported. Deleting arbitrary points however, is not supported, because that would conflict with the size limit since it would be far too painfully slow to remove that point from the linked list that tracks the the order that points were added in. Also, to make sure this doesn't impact speed normally, that list is never even created if no limit was specified. Anyways, the size of the code is getting closer to 500 lines than I'd like it to, so I think this is enough non-optimization features for any sane usage of it. --Rednaxela 04:45, 28 August 2009 (UTC)

I don't know if this is standard or not, but it seems strange that the constructors isn't the very first method in the class. And the method/sub-class ordering is more like... DrussGT's =) They are now ordering by the time you added the code and where, aren't they? I know it isn't going to improve the execution speed, but... » Nat | Talk » 14:40, 28 August 2009 (UTC)

Nah, not ordered by the time added at all. At one point I had the functions for 'bounds' grouped beside the variables, but they kind of drifted apart. There wasn't any real reason for the ordering except that nearby things often had some relevance to eachother. Reformatted that a bit now as to be saner and maintain that relevance-ordering :) --Rednaxela 14:56, 28 August 2009 (UTC)

I've been testing with the pre-limit version of your tree in Portia, and it seems to be working. :) Now with your new version, I do get an error at line double[] location = this.locationStack.pop();: (The method pop() is undefined for the type LinkedList<double[]>). --Positive 15:53, 28 August 2009 (UTC)

Ugh... Any reason why you're on ancient Java 5? Anyway, that method in LinkedList only exists in 6 not 5. Making it Java 5 compatible again... --Rednaxela 16:11, 28 August 2009 (UTC)

Haha, actually I'm on Java 6. I compile everything using the Java 5 library though, so I know for sure I don't make code that's not Java 5 compatible. :) --Positive 16:14, 28 August 2009 (UTC)

Warning! Rounding Errors!

Argh! It seems rounding errors are evil! Evil evil evil! I was toying with my tree in a very lightly segmented gun where exact-same-locations will occur frequently and it did that stupid rampent/infinite branching again. The cause? It turns out to be rounding, indicated by this excerpt from some debugging messages.

...
Split Dimension: 1, Split Value: 1.0, Range: 0.9999999999999999 to 1.0, Width: -1.1102230246251565E-16
Split Dimension: 1, Split Value: 1.0, Range: 0.9999999999999999 to 1.0, Width: -1.1102230246251565E-16
Split Dimension: 1, Split Value: 1.0, Range: 0.9999999999999999 to 1.0, Width: -1.1102230246251565E-16
Split Dimension: 1, Split Value: 1.0, Range: 0.9999999999999999 to 1.0, Width: -1.1102230246251565E-16
Split Dimension: 1, Split Value: 1.0, Range: 0.9999999999999999 to 1.0, Width: -1.1102230246251565E-16
Split Dimension: 1, Split Value: 1.0, Range: 0.9999999999999999 to 1.0, Width: -1.1102230246251565E-16
...

When the only values in the dimension were 1.0, and just BARELY below it, the splitValue would be set to the average of those two values. Due to rounding errors, the average happened to be the same as the higher value... causing the tree to lump all values into the left child node and try branching again, and again, and again :(

So as a warning to those currently using the tree, this obscure sitaution could cause the tree to lock up... I'll release a fix soon --Rednaxela 00:54, 30 August 2009 (UTC)

Well, this sucks, I thought I could fix it simply by making a > into a >= because I thought it always would round one way.... turns out it doesn't... it rounds whatever way it's in the mood for it seems.. bah. Oh and by the way ABC, curse Shadow for hitting such almost-1.0 velocitities as to cause rounding issues :P --Rednaxela 02:22, 30 August 2009 (UTC)

I'm sure there are lots of ways to deal with this, but just a comment on how my insert method handles a similar situation. Values less than the split go to the left, values greater go to the right, and values equal to the split go to alternating sides. One other implication is that when removing a node, you have to check both sides when the value is equal to the split value, but that's easy enough. --Voidious 02:33, 30 August 2009 (UTC)

I guess if you had 19 0.9999's and one 1.0 and it used 1.0 as the split, you'd still have this problem unless the first alternating side also alternated. So I suppose a different special case would probably work a lot better. Another thing that sucks about this, at least if you use the tree the way I do... Rounding every number to, say, 10 digits seems pretty reasonable, but I wouldn't want to do that either, because I count on the fact that the neighbors returned from the tree are the same exact objects I inserted. :-/ --Voidious 02:43, 30 August 2009 (UTC)

(edit conflict) I saw that alternating approach, but I really don't like that approach for several reasons. It increases the balance of the tree very slightly, but it comes at the cost of making each node wider than they need to be. Not only deletes have to search more nodes Voidious, but seraches as well. For example, presume a dimension only has values of 0.0, 0.5, and 1.0 and the first split in the tree is at 0.5. Then the full search has to be repeated completely on both sides, and thus could have a huge impact if such a split happens to be the first split in the whole tree. Anyways, I now have a fix, the solution is: If split value is equal to the maximum node value (will only occur if they're so close that no Double value between could exist), then it sets the split value to the minimum node value instead which guarantees some values will be put in each node. Extensive testing is showing this is working quite nicely :) --Rednaxela 02:48, 30 August 2009 (UTC)

Ah, cool. I agree it can unbalance the tree, but I don't think it makes searches any slower (otherwise). Mine definitely doesn't account for the equal-to-split edge case in its "findLeaf" - I recall thinking it would need to account for that, then realizing it didn't.

When coming back up the tree, you test if the other side of the tree could have a node with a distance to the search point that is lower than some threshold. Since the value could be infinitely close to the split value, you have to just assume it is the split value, right? So while you may take a wrong turn while descending the tree if you hit values equal to the split value, you'll check the other side on the way back up, which you're just as likely to have had to do anyway. In your example, you'd need to search the other side anyway - know what I mean? It's been a while since I wrote my tree, maybe I'm misunderstanding something... =) But I'm pretty sure it's just as accurate and just as fast for searches.

Deletes need to find an actual value that's already in the tree, though, which is a different scenario. (And I don't particularly care how fast deletes are.) --Voidious 03:11, 30 August 2009 (UTC)