kdtree | 易学教程

2D KD Tree and Nearest Neighbour Search

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问题 I'm currently implementing a KD Tree and nearest neighbour search, following the algorithm described here: http://ldots.org/kdtree/ I have come across a couple of different ways to implement a KD Tree, one in which points are stored in internal nodes, and one in which they are only stored in leaf nodes. As I have a very simple use case (all I need to do is construct the tree once, it does not need to be modified), I went for the leaf-only approach is it seemed to be simpler to implement. I

kdtree for geospatial point search

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I'm attempting to find nearest neighbors for point geometry with latitude and longitude information available to me. After much search I concluded that using a kd-tree based approach would be the best option. I have so far tried three different approaches with kd-tree, none of which have worked. Using mercator (UTM) projections. This was least useful as the distance calculation turned out to be completely wrong particularly since the points are spread all over the globe. Using latitude and longitude system of co-ordinates itself. KdTree alternates between lat and long for splitting plane. This

Is kd-tree always balanced?

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问题 I have used kd-tree algoritham and make tree. But i found that tree is not balanced so my question is if we used kd-tree algoritham then that tree is always balanced if not then how can we make it balance ?. We can use another algoritham likes AVL or Red-Black for balancing kd tree ? I have some sample data for that i used kd-tree algoritham but that tree is not balanced. (14,31), (15,32), (17,42), (16,44), (18,52), (16,62) 回答1: This is a fairly broad topic and the questions themselves are

Solid k-d tree implementation in javascript? [closed]

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问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 4 years ago . I'm looking to do a bunch of distance queries in a simulation, and would prefer not to loop over all the points. (N**2 doesn't scale that well, it turns out). Is there a solid k-d tree (or other ball tree, I suppose) implementation in javascript that anyone can recommend? 回答1: Here is another pretty good

PCL kd-tree implementation extremely slow

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I am using Point Cloud Library (PCL) based C++ implementation of kd-tree nearest neighbour(NN) searching. The data set contains about 2.2 million points. I am searching NN points for every other point. The search radius is set at 2.0. To fully compute that, it takes about 12 hours! I am using windows 64 bit machine with 4GB RAM. Is it very common for kd-tree searching? I wonder if there is any other c++ library for 3D point cloud data, which is faster. I heard about ANN C++ library & CGAL, but not sure how fast these are. In short: You can only be sure if you run yourself the time measurements

How to find the closest pairs (Hamming Distance) of a string of binary bins in Ruby without O^2 issues?

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问题 I've got a MongoDB with about 1 million documents in it. These documents all have a string that represents a 256 bit bin of 1s and 0s, like: 0110101010101010110101010101 Ideally, I'd like to query for near binary matches. This means, if the two documents have the following numbers. Yes, this is Hamming Distance. This is NOT currently supported in Mongo. So, I'm forced to do it in the application layer. So, given this, I am trying to find a way to avoid having to do individual Hamming distance

Is kd-tree always balanced?

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I have used kd-tree algoritham and make tree. But i found that tree is not balanced so my question is if we used kd-tree algoritham then that tree is always balanced if not then how can we make it balance ?. We can use another algoritham likes AVL or Red-Black for balancing kd tree ? I have some sample data for that i used kd-tree algoritham but that tree is not balanced. (14,31), (15,32), (17,42), (16,44), (18,52), (16,62) This is a fairly broad topic and the questions themselves are kind of general. Hopefully this will give you some useful insights and material to work with: Kd tree is not

Difference between scipy.spatial.KDTree and scipy.spatial.cKDTree

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问题 What is the difference between these two algorithms? 回答1: cKDTree is a subset of KDTree, implemented in C++ wrapped in Cython, so therefore faster. Each of them is a binary trie, each of whose nodes represents an axis-aligned hyperrectangle. Each node specifies an axis and splits the set of points based on whether their coordinate along that axis is greater than or less than a particular value. but KDTree also supports all-neighbors queries, both with arrays of points and with other kd-trees.

Local maxima in a point cloud

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I have a point cloud C, where each point has an associated value. Lets say the points are in 2-d space, so each point can be represented with the triplet (x, y, v). I'd like to find the subset of points which are local maxima. That is, for some radius R, I would like to find the subset of points S in C such that for any point Pi (with value vi) in S, there is no point Pj in C within R distance of Pi whose value vj is greater that vi. I see how I could do this in O(N^2) time, but that seems wasteful. Is there an efficient way to do this? Side Notes: The source of this problem is that I'm trying

Solid k-d tree implementation in javascript? [closed]

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I'm looking to do a bunch of distance queries in a simulation, and would prefer not to loop over all the points. (N**2 doesn't scale that well, it turns out). Is there a solid k-d tree (or other ball tree, I suppose) implementation in javascript that anyone can recommend? Here is another pretty good implementation that might prove useful (disclaimer - I am the author): https://github.com/ubilabs/kd-tree-javascript Here is a library that I wrote: static-kdtree In Chrome, it is up to several orders of magnitude faster than Ubilabs' kdtree and supports a larger set of queries (orthogonal range