版权声明:本文为博主原创文章,未经博主允许不得转载。 https://blog.csdn.net/u012292754/article/details/86770714
1 借助数组实现二叉堆
Array.java
package heap;
public class Array<E> {
private E[] data;
private int size;
// 构造函数,传入数组的容量capacity构造Array
public Array(int capacity) {
data = (E[]) new Object[capacity];
size = 0;
}
// 无参数的构造函数,默认数组的容量capacity=10
public Array() {
this(10);
}
// 获取数组的容量
public int getCapacity() {
return data.length;
}
// 获取数组中的元素个数
public int getSize() {
return size;
}
// 返回数组是否为空
public boolean isEmpty() {
return size == 0;
}
// 在index索引的位置插入一个新元素e
public void add(int index, E e) {
if (index < 0 || index > size) {
throw new IllegalArgumentException("Add failed. Require index >= 0 and index <= size.");
}
if (size == data.length) {
resize(2 * data.length);
}
for (int i = size - 1; i >= index; i--)
data[i + 1] = data[i];
data[index] = e;
size++;
}
public void addLast(E e) {
add(size, e);
}
public void addFirst(E e) {
add(0, e);
}
// 获取index索引位置的元素
public E get(int index) {
if (index < 0 || index >= size) {
throw new IllegalArgumentException("Get failed. Index is illegal.");
}
return data[index];
}
// 修改index索引位置的元素为e
public void set(int index, E e) {
if (index < 0 || index >= size) {
throw new IllegalArgumentException("Set failed. Index is illegal.");
}
data[index] = e;
}
// 查找数组中是否有元素e
public boolean contains(E e) {
for (int i = 0; i < size; i++) {
if (data[i].equals(e)) {
return true;
}
}
return false;
}
// 查找数组中元素e所在的索引,如果不存在元素e,则返回-1
public int find(E e) {
for (int i = 0; i < size; i++) {
if (data[i].equals(e)) {
return i;
}
}
return -1;
}
// 从数组中删除index位置的元素, 返回删除的元素
public E remove(int index) {
if (index < 0 || index >= size) {
throw new IllegalArgumentException("Remove failed. Index is illegal.");
}
E ret = data[index];
for (int i = index + 1; i < size; i++) {
data[i - 1] = data[i];
}
size--;
data[size] = null; // loitering objects != memory leak
if (size == data.length / 4 && data.length / 2 != 0) {
resize(data.length / 2);
}
return ret;
}
// 从数组中删除第一个元素, 返回删除的元素
public E removeFirst() {
return remove(0);
}
// 从数组中删除最后一个元素, 返回删除的元素
public E removeLast() {
return remove(size - 1);
}
// 从数组中删除元素e
public void removeElement(E e) {
int index = find(e);
if (index != -1) {
remove(index);
}
}
public void swap(int i, int j) {
if (i < 0 || i >= size || j < 0 || j >= size) {
throw new IllegalArgumentException("Index is illegal");
}
E t = data[i];
data[i] = data[j];
data[j] = t;
}
@Override
public String toString() {
StringBuilder res = new StringBuilder();
res.append(String.format("Array: size = %d , capacity = %d\n", size, data.length));
res.append('[');
for (int i = 0; i < size; i++) {
res.append(data[i]);
if (i != size - 1) {
res.append(", ");
}
}
res.append(']');
return res.toString();
}
// 将数组空间的容量变成newCapacity大小
private void resize(int newCapacity) {
E[] newData = (E[]) new Object[newCapacity];
for (int i = 0; i < size; i++) {
newData[i] = data[i];
}
data = newData;
}
}
MaxHeap
package heap;
public class MaxHeap<E extends Comparable<E>> {
private Array<E> data;
public MaxHeap(int capacity) {
data = new Array<E>(capacity);
}
public MaxHeap() {
data = new Array<>();
}
public int size() {
return data.getSize();
}
public boolean isEmpty() {
return data.isEmpty();
}
// 返回完全二叉树的数组表示中,一个索引所表示的元素的父亲节点的索引
private int parent(int index) {
if (index == 0) {
throw new IllegalArgumentException("index-0 does't have parent");
}
return (index - 1) / 2;
}
// 返回完全二叉树的数组表示中,一个索引所表示的元素的左孩子节点的索引
private int leftChild(int index) {
return index * 2 + 1;
}
private int rightChild(int index) {
return index * 2 + 2;
}
public void add(E e) {
data.addLast(e);
siftUp(data.getSize() - 1);
}
private void siftUp(int k) {
while (k > 0 && data.get(parent(k)).compareTo(data.get(k)) < 0) {
data.swap(k, parent(k));
k = parent(k);
}
}
// 查看堆中最大元素
public E findMax() {
if (data.getSize() == 0) {
throw new IllegalArgumentException("heap is empty");
}
return data.get(0);
}
// 取出堆中最大的元素
public E extractMax() {
E ret = findMax();
data.swap(0, data.getSize() - 1);
data.removeLast();
siftDown(0);
return ret;
}
private void siftDown(int k) {
while (leftChild(k) < data.getSize()) {
int j = leftChild(k);
if (j + 1 < data.getSize() &&
data.get(j + 1).compareTo(data.get(j)) > 0) {
j = rightChild(k);
// data[j] 是 leftChild 和 rightChild 中的最大值
}
if (data.get(k).compareTo(data.get(j)) >= 0) {
break;
}
data.swap(k, j);
k = j;
}
}
}
Main.java
package heap;
import java.util.Random;
public class Main {
public static void main(String[] args) {
int n = 1000000;
MaxHeap<Integer> maxHeap = new MaxHeap<>();
Random random = new Random();
for (int i = 0; i < n; i++) {
maxHeap.add(random.nextInt(Integer.MAX_VALUE));
}
int[] arr = new int[n];
for (int i = 0; i < n; i++) {
arr[i] = maxHeap.extractMax();
}
for (int i = 1; i < n; i++) {
if (arr[i - 1] < arr[i]) {
throw new IllegalArgumentException("Error");
}
}
System.out.println("Test MaxHeap completed");
}
}
2 replace
操作
- 取出最大元素后,放入一个新元素;
- 思路(1): 可以先 extractMax ,再 add, 两次 O(logn) 的操作;
- 思路 (2) : 可以直接将对顶元素替换以后 Sift Down ,一次 O(logn) 的操作;
/*
* 取出堆中最大元素,并且替换成元素 e
*
* */
public E replace(E e){
E ret = findMax();
data.set(0,e);
siftDown(0);
return ret;
}
3 heapify
- 将任意数组整理成堆得形状;
- 图中有 5 个叶子节点,倒数第一个非叶子节点是22,从这个节点开始从后向前,每个节点依次进行 Sift Down 操作;
3.1 如何定位最后一个非叶子节点
只需要拿到最后一个节点的索引,找他的父亲节点;
3.2 heapify
算法复杂度
将 n 个元素逐个插入到一个空堆中,复杂度是 O(nlogn)
- heapify 的过程,算法复杂度是 O(n)
3.3 实现
Array.java
public Array(E[] arr){
data = (E[])new Object[arr.length];
for (int i = 0; i < arr.length; i++) {
data[i] = arr[i];
}
size = arr.length;
}
MaxHeap.java
public MaxHeap(E[] arr) {
data = new Array<>(arr);
for (int i = parent(arr.length - 1); i >= 0; i--) {
siftDown(i);
}
}
Main.java
package heap;
import java.util.Random;
public class Main {
private static double testHeap(Integer[] testData, boolean isHeapify) {
long startTime = System.nanoTime();
MaxHeap<Integer> maxHeap;
if (isHeapify) {
maxHeap = new MaxHeap<>(testData);
} else {
maxHeap = new MaxHeap<>();
for (int num : testData) {
maxHeap.add(num);
}
}
int[] arr = new int[testData.length];
for (int i = 0; i < testData.length; i++) {
arr[i] = maxHeap.extractMax();
}
for (int i = 1; i < testData.length; i++) {
if (arr[i - 1] < arr[i]) {
throw new IllegalArgumentException("Error");
}
}
System.out.println("Test MaxHeap completed");
long endTime = System.nanoTime();
return (endTime - startTime) / 1000000000.0;
}
public static void main(String[] args) {
int n = 2000000;
Random random = new Random();
Integer[] testData = new Integer[n];
for (int i = 0; i < n; i++) {
testData[i] = random.nextInt(Integer.MAX_VALUE);
}
double time1 = testHeap(testData, false);
System.out.println("Without heapify: " + time1 + " s");
double time2 = testHeap(testData, true);
System.out.println("With heapify: " + time2 + " s");
}
}