Difference between revisions of "User:Chase-san/Kd-Tree"
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[[Category:Code Snippets|Kd-Tree]] | [[Category:Code Snippets|Kd-Tree]] | ||
− | + | 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 [http://en.wikipedia.org/wiki/Zlib_License ZLIB License]. | |
− | + | Oh yeah, am I the only one that has a Range function? | |
− | + | === KDTreeF === | |
+ | <syntaxhighlight> | ||
+ | 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 KDTree<T> { | ||
+ | protected static final int defaultBucketSize = 48; | ||
− | + | private final int dimensions; | |
− | + | private final int bucketSize; | |
− | + | private NodeKD root; | |
− | |||
− | |||
− | |||
− | |||
/** | /** | ||
− | * | + | * Constructor with value for dimensions. |
* | * | ||
− | * @param | + | * @param dimensions |
− | * - | + | * - Number of dimensions |
*/ | */ | ||
− | public | + | public KDTree(int dimensions) { |
− | this( | + | this.dimensions = dimensions; |
+ | this.bucketSize = defaultBucketSize; | ||
+ | this.root = new NodeKD(); | ||
} | } | ||
/** | /** | ||
− | * | + | * Constructor with value for dimensions and bucket size. |
* | * | ||
− | * @param | + | * @param dimensions |
− | * - | + | * - Number of dimensions |
− | * @param | + | * @param bucket |
− | * - | + | * - Size of the buckets. |
*/ | */ | ||
− | public | + | public KDTree(int dimensions, int bucket) { |
− | + | this.dimensions = dimensions; | |
− | + | this.bucketSize = bucket; | |
− | + | this.root = new NodeKD(); | |
− | |||
− | |||
− | |||
− | |||
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− | |||
} | } | ||
/** | /** | ||
− | * | + | * Add a key and its associated value to the tree. |
* | * | ||
− | * @param | + | * @param key |
− | * - | + | * - Key to add |
+ | * @param val | ||
+ | * - object to add | ||
*/ | */ | ||
− | public void add( | + | public void add(double[] key, T val) { |
− | + | root.addPoint(key, val); | |
− | |||
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− | root. | ||
} | } | ||
/** | /** | ||
− | * | + | * Returns all PointKD within a certain range defined by an upper and lower |
− | * | + | * PointKD. |
* | * | ||
− | * @param | + | * @param low |
− | * @return | + | * - lower bounds of area |
+ | * @param high | ||
+ | * - upper bounds of area | ||
+ | * @return - All PointKD between low and high. | ||
*/ | */ | ||
− | public | + | @SuppressWarnings("unchecked") |
− | + | public List<T> getRange(double[] low, double[] high) { | |
− | + | Object[] objs = root.range(high, low); | |
− | return | + | ArrayList<T> range = new ArrayList<T>(objs.length); |
+ | for(int i=0; i<objs.length; ++i) { | ||
+ | range.add((T)objs[i]); | ||
+ | } | ||
+ | return range; | ||
} | } | ||
/** | /** | ||
− | * | + | * Gets the N nearest neighbors to the given key. |
− | * | + | * |
− | * @param | + | * @param key |
− | * @return | + | * - 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 | + | 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; | |
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} | } | ||
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− | |||
− | + | // 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); | |
− | if ( | + | } else { |
− | + | left.addPoint(key, val); | |
} | } | ||
} | } | ||
− | } | + | } |
− | + | ||
− | double | + | private void addLeafPoint(double[] key, Object val) { |
− | if ( | + | 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 (!heap.isFull() || regionDistSq(data,left.minBounds,left.maxBounds) < heap.getMaxKey()) { | ||
+ | left.nearest(heap, data); | ||
+ | } | ||
+ | } else { | ||
+ | left.nearest(heap, data); | ||
+ | if (right.current == 0) | ||
+ | return; | ||
+ | if (!heap.isFull() || 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; | |
− | tmp = | + | } |
+ | } | ||
+ | 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 | |
− | if ( | + | // 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; | |
− | return | ||
} | } | ||
− | |||
− | |||
− | |||
− | |||
− | + | // 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; | |
− | public | ||
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} | } | ||
+ | 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; | |
− | + | } | |
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− | double | ||
− | for (int i = 0; i < | ||
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} | } | ||
− | + | ||
− | for (int i = 0; i < current; | + | 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]; | ||
} | } | ||
} | } | ||
− | |||
− | |||
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} | } | ||
+ | |||
+ | /* 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; | ||
+ | } | ||
} | } | ||
− | </ | + | </syntaxhighlight> |
− | |||
− | === | + | === ResultHeap === |
− | < | + | <syntaxhighlight> |
package org.csdgn.util; | package org.csdgn.util; | ||
/** | /** | ||
− | + | * @author Chase | |
− | |||
− | |||
− | * @author | ||
* | * | ||
+ | * @param <T> | ||
*/ | */ | ||
− | public class | + | 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; | |
− | |||
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} | } | ||
− | + | 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]; | |
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− | public | ||
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} | } | ||
− | + | ||
− | + | @SuppressWarnings("unchecked") | |
− | + | public T removeMax() { | |
− | + | if(isEmpty()) return null; | |
− | + | return (T)data[--size]; | |
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} | } | ||
− | + | public boolean isEmpty() { | |
− | + | return size == 0; | |
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− | + | public boolean isFull() { | |
− | + | return size == capacity; | |
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− | + | public int size() { | |
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− | + | public int capacity() { | |
− | + | return capacity; | |
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} | } | ||
− | </ | + | </syntaxhighlight> |
Latest revision as of 21:00, 7 November 2012
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 KDTree<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 KDTree(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 KDTree(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) {
Object[] objs = root.range(high, low);
ArrayList<T> range = new ArrayList<T>(objs.length);
for(int i=0; i<objs.length; ++i) {
range.add((T)objs[i]);
}
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 (!heap.isFull() || regionDistSq(data,left.minBounds,left.maxBounds) < heap.getMaxKey()) {
left.nearest(heap, data);
}
} else {
left.nearest(heap, data);
if (right.current == 0)
return;
if (!heap.isFull() || 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;
}
}