Given a non-empty array of integers, return the k most frequent elements.
Example 1:
Input: nums = [1,1,1,2,2,3], k = 2 Output: [1,2]Example 2:
Input: nums = [1], k = 1 Output: [1]
给定一个非空的整数数组,返回其中出现频率前 k 高的元素。
示例 1:
输入: nums = [1,1,1,2,2,3], k = 2 输出: [1,2]示例 2:
输入: nums = [1], k = 1 输出: [1]
import java.util.*;
public class Solution5 {
public List<Integer> topKFrequent(int[] nums, int k) {
TreeMap<Integer, Integer> map = new TreeMap<>();
for(int num: nums){
if(map.containsKey(num))
map.put(num, map.get(num) + 1);
else
map.put(num, 1);
}PriorityQueue<Integer> pq = new PriorityQueue<>(
(a, b) -> map.get(a) - map.get(b) //这里相当于匿名类 lamda表达式 后面->为返回值
);
for(int key: map.keySet()){
if(pq.size() < k)
pq.add(key);
else if(map.get(key) > map.get(pq.peek())){
pq.remove();
pq.add(key);
}
}LinkedList<Integer> res = new LinkedList<>();
while(!pq.isEmpty())
res.add(pq.remove());
return res;
}private static void printList(List<Integer> nums){
for(Integer num: nums)
System.out.print(num + " ");
System.out.println();
}public static void main(String[] args) {
int[] nums = {1, 1, 1, 2, 2, 3};
int k = 2;
printList((new Solution()).topKFrequent(nums, k));
}
}
import java.util.LinkedList;
import java.util.List;
import java.util.TreeMap;class Solution {
private 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);
}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;
}// 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 ++;
}// 向所有元素后添加一个新元素
public void addLast(E e){
add(size, e);
}// 在所有元素前添加一个新元素
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 leakif(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;
}
}private class MaxHeap<E extends Comparable<E>> {
private Array<E> data;
public MaxHeap(int capacity){
data = new Array<>(capacity);
}public MaxHeap(){
data = new Array<>();
}public MaxHeap(E[] arr){
data = new Array<>(arr);
for(int i = parent(arr.length - 1) ; i >= 0 ; i --)
siftDown(i);
}// 返回堆中的元素个数
public int size(){
return data.getSize();
}// 返回一个布尔值, 表示堆中是否为空
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 doesn'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;
}// 返回完全二叉树的数组表示中,一个索引所表示的元素的右孩子节点的索引
private int rightChild(int index){
return index * 2 + 2;
}// 向堆中添加元素
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);
}
}// 看堆中的最大元素
public E findMax(){
if(data.getSize() == 0)
throw new IllegalArgumentException("Can not findMax when heap is empty.");
return data.get(0);
}// 取出堆中最大元素
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); // 在此轮循环中,data[k]和data[j]交换位置
if( j + 1 < data.getSize() &&
data.get(j + 1).compareTo(data.get(j)) > 0 )
j ++;
// 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;
}
}// 取出堆中的最大元素,并且替换成元素e
public E replace(E e){E ret = findMax();
data.set(0, e);
siftDown(0);
return ret;
}
}private interface Queue<E> {
int getSize();
boolean isEmpty();
void enqueue(E e);
E dequeue();
E getFront();
}private class PriorityQueue<E extends Comparable<E>> implements Queue<E> {
private MaxHeap<E> maxHeap;
public PriorityQueue(){
maxHeap = new MaxHeap<>();
}@Override
public int getSize(){
return maxHeap.size();
}@Override
public boolean isEmpty(){
return maxHeap.isEmpty();
}@Override
public E getFront(){
return maxHeap.findMax();
}@Override
public void enqueue(E e){
maxHeap.add(e);
}@Override
public E dequeue(){
return maxHeap.extractMax();
}
}private class Freq implements Comparable<Freq>{
public int e, freq;
public Freq(int e, int freq){
this.e = e;
this.freq = freq;
}@Override
public int compareTo(Freq another){
if(this.freq < another.freq)
return 1;
else if(this.freq > another.freq)
return -1;
else
return 0;
}
}public List<Integer> topKFrequent(int[] nums, int k) {
TreeMap<Integer, Integer> map = new TreeMap<>();
for(int num: nums){
if(map.containsKey(num))
map.put(num, map.get(num) + 1);
else
map.put(num, 1);
}PriorityQueue<Freq> pq = new PriorityQueue<>();
for(int key: map.keySet()){
if(pq.getSize() < k)
pq.enqueue(new Freq(key, map.get(key)));
else if(map.get(key) > pq.getFront().freq){
pq.dequeue();
pq.enqueue(new Freq(key, map.get(key)));
}
}LinkedList<Integer> res = new LinkedList<>();
while(!pq.isEmpty())
res.add(pq.dequeue().e);
return res;
}private static void printList(List<Integer> nums){
for(Integer num: nums)
System.out.print(num + " ");
System.out.println();
}public static void main(String[] args) {
int[] nums = {1, 1, 1, 2, 2, 3};
int k = 2;
printList((new Solution()).topKFrequent(nums, k));
}
}