User:Chase-san/Kd-Tree
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Everyone and their brother has one of these now, me and Simonton started it, but I was to inexperienced to get anything written, I took an hour or two to rewrite it today, because I am no longer completely terrible at these things. So here is mine if you care to see it.
This and all my other code in which I display on the robowiki falls under the ZLIB License.
Oh yeah, am I the only one that has a Range function?
KDTreeF
package org.csdgn.util;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
/**
* This is a KD Bucket Tree, for fast sorting and searching of K dimensional
* data.
*
* @author Chase
*
*/
public class KDTreeF<T> {
protected static final int defaultBucketSize = 48;
private final int dimensions;
private final int bucketSize;
private NodeKD root;
/**
* Constructor with value for dimensions.
*
* @param dimensions
* - Number of dimensions
*/
public KDTreeF(int dimensions) {
this.dimensions = dimensions;
this.bucketSize = defaultBucketSize;
this.root = new NodeKD();
}
/**
* Constructor with value for dimensions and bucket size.
*
* @param dimensions
* - Number of dimensions
* @param bucket
* - Size of the buckets.
*/
public KDTreeF(int dimensions, int bucket) {
this.dimensions = dimensions;
this.bucketSize = bucket;
this.root = new NodeKD();
}
/**
* Add a key and its associated value to the tree.
*
* @param key
* - Key to add
* @param val
* - object to add
*/
public void add(double[] key, T val) {
root.addPoint(key, val);
}
/**
* Returns all PointKD within a certain range defined by an upper and lower
* PointKD.
*
* @param low
* - lower bounds of area
* @param high
* - upper bounds of area
* @return - All PointKD between low and high.
*/
@SuppressWarnings("unchecked")
public List<T> getRange(double[] low, double[] high) {
ArrayList<T> range = new ArrayList<T>();
for (Object o : root.range(high, low)) {
range.add((T) o);
}
return range;
}
/**
* Gets the N nearest neighbors to the given key.
*
* @param key
* - Key
* @param num
* - Number of results
* @return Array of Item Objects, distances within the items are the square
* of the actual distance between them and the key
*/
public ResultHeap<T> getNearestNeighbors(double[] key, int num) {
ResultHeap<T> heap = new ResultHeap<T>(num);
root.nearest(heap, key);
return heap;
}
// Internal tree node
private class NodeKD {
private NodeKD left, right;
private double[] maxBounds, minBounds;
private Object[] bucketValues;
private double[][] bucketKeys;
private boolean isLeaf;
private int current, sliceDimension;
private double slice;
private NodeKD() {
bucketValues = new Object[bucketSize];
bucketKeys = new double[bucketSize][];
left = right = null;
maxBounds = minBounds = null;
isLeaf = true;
current = 0;
}
// what it says on the tin
private void addPoint(double[] key, Object val) {
if(isLeaf) {
addLeafPoint(key,val);
} else {
extendBounds(key);
if (key[sliceDimension] > slice) {
right.addPoint(key, val);
} else {
left.addPoint(key, val);
}
}
}
private void addLeafPoint(double[] key, Object val) {
extendBounds(key);
if (current + 1 > bucketSize) {
splitLeaf();
addPoint(key, val);
return;
}
bucketKeys[current] = key;
bucketValues[current] = val;
++current;
}
/**
* Find the nearest neighbor recursively.
*/
@SuppressWarnings("unchecked")
private void nearest(ResultHeap<T> heap, double[] data) {
if(current == 0)
return;
if(isLeaf) {
//IS LEAF
for (int i = 0; i < current; i++) {
double dist = pointDistSq(bucketKeys[i], data);
heap.offer(dist, (T) bucketValues[i]);
}
} else {
//IS BRANCH
if (data[sliceDimension] > slice) {
right.nearest(heap, data);
if(left.current == 0)
return;
if (regionDistSq(data,left.minBounds,left.maxBounds) < heap.getMaxKey()) {
left.nearest(heap, data);
}
} else {
left.nearest(heap, data);
if (right.current == 0)
return;
if (regionDistSq(data,right.minBounds,right.maxBounds) < heap.getMaxKey()) {
right.nearest(heap, data);
}
}
}
}
// gets all items from within a range
private Object[] range(double[] upper, double[] lower) {
if (bucketValues == null) {
// Branch
Object[] tmp = new Object[0];
if (intersects(upper, lower, left.maxBounds, left.minBounds)) {
Object[] tmpl = left.range(upper, lower);
if (0 == tmp.length) tmp = tmpl;
}
if (intersects(upper, lower, right.maxBounds, right.minBounds)) {
Object[] tmpr = right.range(upper, lower);
if (0 == tmp.length)
tmp = tmpr;
else if (0 < tmpr.length) {
Object[] tmp2 = new Object[tmp.length + tmpr.length];
System.arraycopy(tmp, 0, tmp2, 0, tmp.length);
System.arraycopy(tmpr, 0, tmp2, tmp.length, tmpr.length);
tmp = tmp2;
}
}
return tmp;
}
// Leaf
Object[] tmp = new Object[current];
int n = 0;
for (int i = 0; i < current; i++) {
if (contains(upper, lower, bucketKeys[i])) {
tmp[n++] = bucketValues[i];
}
}
Object[] tmp2 = new Object[n];
System.arraycopy(tmp, 0, tmp2, 0, n);
return tmp2;
}
// These are helper functions from here down
// check if this hyper rectangle contains a give hyper-point
public boolean contains(double[] upper, double[] lower, double[] point) {
if (current == 0) return false;
for (int i = 0; i < point.length; ++i) {
if (point[i] > upper[i] || point[i] < lower[i]) return false;
}
return true;
}
// checks if two hyper-rectangles intersect
public boolean intersects(double[] up0, double[] low0, double[] up1, double[] low1) {
for (int i = 0; i < up0.length; ++i) {
if (up1[i] < low0[i] || low1[i] > up0[i]) return false;
}
return true;
}
private void splitLeaf() {
double bestRange = 0;
for(int i=0;i<dimensions;++i) {
double range = maxBounds[i] - minBounds[i];
if(range > bestRange) {
sliceDimension = i;
bestRange = range;
}
}
left = new NodeKD();
right = new NodeKD();
slice = (maxBounds[sliceDimension] + minBounds[sliceDimension]) * 0.5;
for (int i = 0; i < current; ++i) {
if (bucketKeys[i][sliceDimension] > slice) {
right.addLeafPoint(bucketKeys[i], bucketValues[i]);
} else {
left.addLeafPoint(bucketKeys[i], bucketValues[i]);
}
}
bucketKeys = null;
bucketValues = null;
isLeaf = false;
}
// expands this hyper rectangle
private void extendBounds(double[] key) {
if (maxBounds == null) {
maxBounds = Arrays.copyOf(key, dimensions);
minBounds = Arrays.copyOf(key, dimensions);
return;
}
for (int i = 0; i < key.length; ++i) {
if (maxBounds[i] < key[i]) maxBounds[i] = key[i];
if (minBounds[i] > key[i]) minBounds[i] = key[i];
}
}
}
/* I may have borrowed these from an early version of Red's tree. I however forget. */
private static final double pointDistSq(double[] p1, double[] p2) {
double d = 0;
double q = 0;
for (int i = 0; i < p1.length; i++) {
d += (q=(p1[i] - p2[i]))*q;
}
return d;
}
private static final double regionDistSq(double[] point, double[] min, double[] max) {
double d = 0;
double q = 0;
for (int i = 0; i < point.length; i++) {
if (point[i] > max[i]) {
d += (q = (point[i] - max[i]))*q;
} else if (point[i] < min[i]) {
d += (q = (point[i] - min[i]))*q;
}
}
return d;
}
}ResultHeap
package org.csdgn.util;
/**
* @author Chase
*
* @param <T>
*/
public class ResultHeap<T> {
private Object[] data;
private double[] keys;
private int capacity;
private int size;
protected ResultHeap(int capacity) {
this.data = new Object[capacity];
this.keys = new double[capacity];
this.capacity = capacity;
this.size = 0;
}
protected void offer(double key, T value) {
int i = size;
for (; i > 0 && keys[i - 1] > key; --i);
if (i >= capacity) return;
if (size < capacity) ++size;
int j = i + 1;
System.arraycopy(keys, i, keys, j, size - j);
keys[i] = key;
System.arraycopy(data, i, data, j, size - j);
data[i] = value;
}
public double getMaxKey() {
return keys[size - 1];
}
@SuppressWarnings("unchecked")
public T removeMax() {
if(isEmpty()) return null;
return (T)data[--size];
}
public boolean isEmpty() {
return size == 0;
}
public boolean isFull() {
return size == capacity;
}
public int size() {
return size;
}
public int capacity() {
return capacity;
}
}
