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kd-tree
K-D tree implementation.
Documentation
This library implements a K-D tree, which is a data structure for organizing and searching points in k-dimensional space.
The K-D tree is a binary search tree in which every branching node contains a k-dimensional point, and every leaf node contains a set of points. Every branching node represents a splitting hyperplane that divides the space into two parts, known as half-spaces.
Points to the left of the splitting hyperplane are contained in the left subtree of the node and points right of the hyperplane are contained in the right subtree. The splitting hyperplane is chosen so as to be perpendicular to one of the axes in the k-dimensional space. The axis at each branching level is chosen in a round-robin fashion. For instance, in 3-D space, at level 0, the chosen axis is X, so points are divided according to their X-coordinates; at level 1, the chosen axis is Y, so the points are divided according to their Y-coordinates; at the next branch level the chosen axis is Z, and so on.
K-dimensional point space
Module kspace provides facilities for managament of K-dimensional point spaces.
- make-space:procedure
Given a list of coordinate collections of length K, constructs a yasos K-dimensional point space object. The coordinate collections can be SRFI-4 f32vectors, or collection objects as defined in the yasos collections module.
- space?procedure
K-dimensional point space predicate.
- dimensionprocedure
Returns the dimensionality of the point space.
- pointprocedure
Returns the coordinates of the point at the given index.
- coordprocedure
Returns the k'th coordinate of i'th point, starting from 0.
- compare-coordprocedure
Given the indices of two points and a coordinate index, compares the respective coordinates of the two points and returns -1, 0, or 1, depending on whether the coordinates are less than, equal, or greater than each other.
- squared-distanceprocedure
Returns the square of the Euclidean distance between the points at the given indices.
- compare-distanceprocedure
Compares the square of the Euclidean distance between the points at the given indices.
K-D tree interface
Constructors
- make-kd-tree:procedure
Given a kspace object, constructs and returns a yasos spatial map object.
Predicates
- spatial-map?procedure
Returns #t if the given object is a spatial map, #f otherwise.
- empty?procedure
Returns #t if the given spatial map object is empty, #f otherwise.
- kd-tree-is-valid?procedure
Checks whether the K-D tree property holds for the given spatial map. Specifically, it tests that all points in the left subtree lie to the left of the plane, p is on the plane, and all points in the right subtree lie to the right.
- kd-tree-all-subtrees-are-valid?procedure
Checks whether the K-D tree property holds for the given spatial map and all subtrees.
Accessors
- get-kspaceprocedure
Returns the underlying kspace object of the map.
- spatial-map->listprocedure
Returns a list with the points contained in the spatial map.
Query procedures
- nearest-neighborprocedure
Nearest neighbor of a point.
- near-neighborsprocedure
Neighbors of a point within radius r.
- k-nearest-neighborsprocedure
K nearest neighbors of a point.
- sliceprocedure
Returns all points between two planes.
Combinators
- spatial-map-for-eachprocedure
Point iterator.
- spatial-map-fold-rightprocedure
Fold on points.
- spatial-map-fold-right*procedure
Fold on points and their indices.
Modifiers
- kd-tree-removeprocedure
Examples
(import scheme (chicken base) yasos random-mtzig kspace kd-tree) (let* ( (n (inexact->exact 1e5)) (k 40) (r 1.0) (randst (init 9)) ;; generate random coordinates (xs (randn/f32! n randst)) (ys (randn/f32! n randst)) (zs (randn/f32! n randst)) ;; create a kspace (pts (list xs ys zs)) (kspace3d (make-space pts)) ;; create the spatial map (kdt (make-kd-tree kspace3d)) ;; choose a random point index (xi (inexact->exact (modulo (random! randst) n))) ;; retrieve the coordinates of the chosen point (x (point kspace3d xi)) ) (print "nearest-neighbor of " x ": " (nearest-neighbor kdt x)) (print k " nearest neighbors of " x ": " (k-nearest-neighbors kdt x k)) (print "near neighbors of " x " within " r ": " (near-neighbors kdt k r)) )
Repository
https://github.com/iraikov/chicken-kdtree
Version history
- 6.0 : refactored to use yasos, ported to CHICKEN 5
- 5.0 : added list->kd-tree* procedure to KdTree class
- 4.1-4.8 : Using f64vector for internal point representation
- 4.0-4.1 : Added with-distance? flag to kd-tree-near-neighbors
- 3.2 : Bug fix in kd-tree-near-neighbors
- 2.0 : Improvements to internal representation
- 1.0 : Initial release
License
Copyright 2012-2019 Ivan Raikov This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. A full copy of the GPL license can be found at http://www.gnu.org/licenses/.