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Questions tagged [kdtree]

A k-d-tree (k-dimensional tree) is a data structure for storing points in multidimensional space. They can be used to efficiently query for whether a point exists, as well as to do Euclidean nearest-neighbor searches and searches inside of hyperdimensional rectangular regions.

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Neighbour search with kd trees

I have a dataset of points in R^3. I'm able to build a kd-tree with python's subpackage spatial (see here) and performing a neighbour search (all points within distance r from the query point). What I don't get is the following: When I build the…
KungFury
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SciPy KDTree distance units?

Let's say I have and array, where column 1 is in feet, column 2 is in feet, and column 3 is in seconds. For example: x = [50 40 30] I then have another array, y, with the same units and same number of columns, but many rows. I then turn it into a…
user1566200
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Why need to alternate dimension in kd-tree construction

I have a question regarding the way to partition the spaces in kd-tree algorithm. Assuming I have points in the plane, with (x,y) coordinate. Assuming we're not in a particular situation when points are in the same line. I was thinking why we need…
ctNGUYEN
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Conditional jump or move depends on uninitialised value(s) and Segmentation fault

I'm using a ANN library (kdtree) and I have a problem creating and destroying these objects: This is my constructor: myKdtree::myKdtree(vector *P){ int nnPts = P->size(); dataPts = annAllocPts(P->size(), DIM); for (int i = 0; i…
froure
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Fast k-NN search over bag-of-words models

I have a large amount of documents of equal size. For each of those documents I'm building a bag of words model (BOW). Number of possible words in all documents is limited and large (2^16 for example). Generally speaking, I have N histograms of size…
Evgeny Lazin
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KdTree C implementation resulting in core dump

I'm dealing with a core dump issue to which whom I cannot find a solution. Any kind of help would be appreciated 'cause I'm getting hopeless. I assume the error appears when getting to the second execution of the building function but I'm clueless…
Tomasz Szymanek
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Different return and coordinate types in nanoflann radius search

I'm trying to use nanoflann in a project and am looking at the vector-of-vector and radius search examples. I can't find a way to perform a radius search with a different data type than the coordinate type. For example, my coordinates are vectors…
thekamz
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Data structure for spatial queries (kNN) on dynamic data

For spatial queries like nearest neighbor search, in theory, KD tree or Voronoi or R tree(or one of its variants) work. But what is the preferred data structure/algo for dynamic data?
mithya
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C++: looking for thread based a parallel kd tree library

Are there some implementation for KD-Tree on shared memory machines? thanks Arman.
Arman
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KD-Tree on secondary memory?

I know some of the range searching data structure, for example kd-tree, Range tree and quad-tree. But all the implementation is in memory, how can I implementation them on secondary memory with high performance I/O efficiency? Here is the…
Zhao Yuhao
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Finding nearest neighbor(s) in a KD Tree

Warning: Fairly long question, perhaps too long. If so, I apologize. I'm working on a program involving a nearest neighbor(s) search of a kd tree (in this example, it is an 11 dimensional tree with 3961 individual points). We've only just learned…
user2993631
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Data structure for irregular grid

Im wondering what is the best data structure for grid containing different sized rectangles/squares as game map sectors. I need to acces object within that grid by simple xyz coordinates. searched for KdTrees, but they seem to find nearest object,…
user2550696
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Python optomise nearest neighbour for large arrays

I have an array of points in 4D space (my array is roughly 1,000,000 long). For each value in my array I need to find the kth (where k = 81) nearest neighbours I then do some further code based on that.. [in brief, I'm effectively trying to extend…
CastleH
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Modify this algorithm for Nearest Neighbour Search (NNS) to perform Approximate-NNS

From the slides of a course, I found these: Given a set P in R^D, and a query point q, it's NN is point p_0 in P, where: dist(p_0, q) <= dist(p, q), for every p in P. Similarly, with an approximation factor 1 > ε > 0, the ε-NN is p_0, such…
gsamaras
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Combining items into fixed sized groups for k-d tree

I'm using a k-d tree for spacial partitioning in a ray-tracer. I want to combine near-by primitives into fixed-sized groups so the data in each group can be deinterleaved and processed simultaneously using SIMD instructions. What is a good fast…
Rouslan
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