java栈队列优先队列算法
栈
public class Solution {
//将做方向的括号放入栈中
Stack<Character> stack = new Stack<Character>();
for( int i = 0 ; i < s.length() ; i ++ )
if( s.charAt(i) == '(' || s.charAt(i) == '{' || s.charAt(i) == '[')
stack.push(s.charAt(i));
//遇到右方向的括号,取出栈中的元素,判断是否匹配
else{
if( stack.size() == 0 )
return false;
Character c = stack.pop();
Character match;
if( s.charAt(i) == ')' )
match = '(';
else if( s.charAt(i) == ']' )
match = '[';
else{
assert s.charAt(i) == '}';
match = '{';
}
if(c != match)
return false;
}
if( stack.size() != 0 )
return false;
return true;
}
}
队列
队列
import java.util.LinkedList;
public class Solution {
LinkedList<Pair<Integer, Integer>> queue = new LinkedList<Pair<Integer, Integer>>();
queue.addLast(new Pair<Integer, Integer>(n, 0));
boolean[] visited = new boolean[n+1];
visited[n] = true;
while(!queue.isEmpty()){
Pair<Integer, Integer> front = queue.removeFirst();
int num = front.getKey();
int step = front.getValue();
//判断是否到达了0,根据到达0判断经过的路径
if(num == 0)
return step;
//查看到达某一路径是否还有剩余的步数
for(int i = 1 ; num - i*i >= 0 ; i ++)
if(!visited[num - i * i]){
queue.addLast(new Pair(num - i * i, step + 1));
visited[num - i * i] = true;
}
}
}
优先队列根据个位数排序
public static void main(String[] args) {
// 默认的PriorityQueue, 底层是最小堆
PriorityQueue<Integer> pq = new PriorityQueue<Integer>();
for(int i = 0 ; i < 10 ; i ++){
int num = (int)(Math.random() * 100);
pq.add(num);
System.out.println("insert " + num + " in priority queue.");
}
while (!pq.isEmpty())
System.out.print(pq.poll() + " ");
System.out.println();
System.out.println();
// 使用lambda表达式,创建底层是最大堆的PriorityQueue
PriorityQueue<Integer> pq2 = new PriorityQueue<Integer>(10, (a, b) -> b - a);
for(int i = 0 ; i < 10 ; i ++){
int num = (int)(Math.random() * 100);
pq2.add(num);
System.out.println("insert " + num + " in priority queue.");
}
while (!pq2.isEmpty())
System.out.print(pq2.poll() + " ");
System.out.println();
System.out.println();
// 使用自定义的Comparator,创建个性化的PriorityQueue
// 注意:也可以使用lambda表达式。在这里只是为了演示PriorityQueue的不同用法
// 同理,上一个例子也可以使用自定义的Comparator的方式完成
class myCmp implements Comparator<Integer>{
@Override
public int compare(Integer a, Integer b){
if(a%10 != b%10)
return a%10 - b%10;
return a - b;
}
}
PriorityQueue<Integer> pq3 = new PriorityQueue<Integer>(10, new myCmp());
for(int i = 0 ; i < 10 ; i ++){
int num = (int)(Math.random() * 100);
pq3.add(num);
System.out.println("insert " + num + " in priority queue.");
}
while (!pq3.isEmpty())
System.out.print(pq3.poll() + " ");
System.out.println();
System.out.println();
}
import java.util.LinkedList;
public class Solution {
//存入数据的同时记录频率
if(k <= 0)
throw new IllegalArgumentException("k should be greater than 0");
// 统计每个元素出现的频率
HashMap<Integer, Integer> freq = new HashMap<Integer, Integer>();
for(int i = 0 ; i < nums.length ; i ++)
if(freq.containsKey(nums[i]))
freq.put(nums[i], freq.get(nums[i]) + 1);
else
freq.put(nums[i], 1);
if(k > freq.size())
throw new IllegalArgumentException("k should be less than the number of unique numbers in nums");
//对所有的数据记录频率之后,对频率进行排序,记录频率前N的数据
private class PairComparator implements Comparator<Pair<Integer, Integer>>{
@Override
public int compare(Pair<Integer, Integer> p1, Pair<Integer, Integer> p2){
if(p1.getKey() != p2.getKey())
return p1.getKey() - p2.getKey();
return p1.getValue() - p2.getValue();
}
}
// 扫描freq,维护当前出现频率最高的k个元素
// 在优先队列中,按照频率排序,所以数据对是 (频率,元素) 的形式
PriorityQueue<Pair<Integer, Integer>> pq = new PriorityQueue<Pair<Integer, Integer>>(new PairComparator());
for(Integer num: freq.keySet()){
int numFreq = freq.get(num);
if(pq.size() == k){
if(numFreq > pq.peek().getKey()){
pq.poll();
pq.add(new Pair(numFreq, num));
}
}
else
pq.add(new Pair(numFreq, num));
}
ArrayList<Integer> res = new ArrayList<Integer>();
while(!pq.isEmpty())
res.add(pq.poll().getValue());
return res;
}
}