哈夫曼树的用途十分广泛,典型的一道面试题“分金条的最小花费”就是哈夫曼编码的变型,详情可以参看《程序员代码面试指南》P421。
package com.gxu.dawnlab_algorithm7;
import java.util.Comparator;
import java.util.PriorityQueue;
/**
* 分金条的最小花费
* @author junbin
*
* 2019年7月11日
*/
public class Less_Money {
public static int lessMoney(int[] arr) {
PriorityQueue<Integer> pQ = new PriorityQueue<>(); //优先级队列就是堆结构,而且默认是小根堆结构
for (int i = 0; i < arr.length; i++) {
pQ.add(arr[i]);
}
int sum = 0;
int cur = 0;
while (pQ.size() > 1) {
cur = pQ.poll() + pQ.poll();
sum += cur;
pQ.add(cur);
}
return sum;
}
public static class MinheapComparator implements Comparator<Integer> {
@Override
public int compare(Integer o1, Integer o2) {
return o1 - o2; // < 0 o1 < o2 负数
}
}
public static class MaxheapComparator implements Comparator<Integer> {
@Override
public int compare(Integer o1, Integer o2) {
return o2 - o1; // < o2 < o1
}
}
public static void main(String[] args) {
// solution
int[] arr = { 6, 7, 8, 9 };
System.out.println(lessMoney(arr));
int[] arrForHeap = { 3, 5, 2, 7, 0, 1, 6, 4 };
// min heap
PriorityQueue<Integer> minQ1 = new PriorityQueue<>();
for (int i = 0; i < arrForHeap.length; i++) {
minQ1.add(arrForHeap[i]);
}
while (!minQ1.isEmpty()) {
System.out.print(minQ1.poll() + " ");
}
System.out.println();
// min heap use Comparator
PriorityQueue<Integer> minQ2 = new PriorityQueue<>(new MinheapComparator());
for (int i = 0; i < arrForHeap.length; i++) {
minQ2.add(arrForHeap[i]);
}
while (!minQ2.isEmpty()) {
System.out.print(minQ2.poll() + " ");
}
System.out.println();
// max heap use Comparator
PriorityQueue<Integer> maxQ = new PriorityQueue<>(new MaxheapComparator());
for (int i = 0; i < arrForHeap.length; i++) {
maxQ.add(arrForHeap[i]);
}
while (!maxQ.isEmpty()) {
System.out.print(maxQ.poll() + " ");
}
}
}