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The intention of this mex-file was to reduce the computational overhead of
preprocessing for nearest neighbor or range searching. With nn_prepare it is possible
to do the preprocessing for a given point set only once and save the created tree
structure into a Matlab variable. This Matlab variable, usually called
*atria*, can then be used for repeated neighbor searches on the same point set.
Most mex-files that rely on nearest neighbor or range search offer the possibility
to use this variable atria as optional input argument. However, if the underlying
point set is altered in any way, the proprocessing has to be repeated for the new point
set. If the preprocessing output does not belong to the given point set, wrong results
or program termination may occur.

**Syntax:**

`atria = nn_prepare(pointset)``atria = nn_prepare(pointset, metric)``atria = nn_prepare(pointset, metric, clustersize)`

**Input arguments:**

`pointset`- a`N`by`D`double matrix containing the coordinates of the point set, organized as`N`points of dimension`D``metric`- (optional) either 'euclidian' or 'maximum' (default is 'euclidian')`clustersize`- (optional) threshold for clustering algorithm, defaults to 64

**Example:**

pointset = rand(40000, 3); atria = nn_prepare(pointset); [c, d] = corrsum(atria, pointset, 1:17:40000, 0.05, 0); plot(log(d), log(c)) D = takens_estimator(atria, pointset, 1:17:40000, 0.05, 0)

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