414. Third Maximum Number

本文介绍了一种在非空整数数组中查找第三大数值的方法,并提供两种解决方案:一种使用排序,另一种通过维护一个有序的三元素数组实现,后者达到了O(n)的时间复杂度要求。

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Given a non-empty array of integers, return the third maximum number in this array. If it does not exist, return the maximum number. The time complexity must be in O(n).

Example 1:

Input: [3, 2, 1]

Output: 1

Explanation: The third maximum is 1.

Example 2:

Input: [1, 2]

Output: 2

Explanation: The third maximum does not exist, so the maximum (2) is returned instead.

Example 3:

Input: [2, 2, 3, 1]

Output: 1

Explanation: Note that the third maximum here means the third maximum distinct number.
Both numbers with value 2 are both considered as second maximum.
给一个非空数组,找第三大的数,第一想到的就是先排序,再输出第三大的数。基于这个思想,见下面代码:

public class Solution {
    public int thirdMax(int[] nums) {
        if (nums.length == 0) {
            return 0;
        }
        Arrays.sort(nums);
        int count = 0;
        int i = nums.length - 1;
        while (i > 0) {
            if (nums[i] != nums[i - 1]) {
                count ++;
            }
            if (count >= 2) 
                break;
            i --;
        }
        if (count < 2) {
            return nums[nums.length - 1];
        } else {
            return nums[i - 1];
        }
    }
}
但是Array.sort() 的时间复杂度是O(nlogn),不符合题目要求。所以想到下面的解法,用一个数组保存top3的数,按升序保存,每次改变 top3[0]的值,重新排列数组,这样可以保证top3大的数永远在后三位,且为升序排列。代码如下:

public class Solution {
    public int thirdMax(int[] nums) {
        if (nums.length == 0) {
            return 0;
        }
        int[] top3 = {Integer.MIN_VALUE, Integer.MIN_VALUE, Integer.MIN_VALUE, Integer.MIN_VALUE};
        HashSet<Integer> hs = new HashSet<Integer>();
        int i = 0;
        int p = 0;
        for (; i < nums.length; i ++) {
            if (!hs.contains(nums[i])) {
                hs.add(nums[i]);
                top3[0] = nums[i];
                //Array.sort()  O(nlogn)
                Arrays.sort(top3);
                p ++;
            }
        }
        if (p < 3) {
            return top3[3];
        } else {
            return top3[1];
        }
    }
}
上面代码的时间复杂度是O(n),符合要求。




Yousef has an array a of size n . He wants to partition the array into one or more contiguous segments such that each element ai belongs to exactly one segment. A partition is called cool if, for every segment bj , all elements in bj also appear in bj+1 (if it exists). That is, every element in a segment must also be present in the segment following it. For example, if a=[1,2,2,3,1,5] , a cool partition Yousef can make is b1=[1,2] , b2=[2,3,1,5] . This is a cool partition because every element in b1 (which are 1 and 2 ) also appears in b2 . In contrast, b1=[1,2,2] , b2=[3,1,5] is not a cool partition, since 2 appears in b1 but not in b2 . Note that after partitioning the array, you do not change the order of the segments. Also, note that if an element appears several times in some segment bj , it only needs to appear at least once in bj+1 . Your task is to help Yousef by finding the maximum number of segments that make a cool partition. Input The first line of the input contains integer t (1≤t≤104 ) — the number of test cases. The first line of each test case contains an integer n (1≤n≤2⋅105 ) — the size of the array. The second line of each test case contains n integers a1,a2,…,an (1≤ai≤n ) — the elements of the array. It is guaranteed that the sum of n over all test cases doesn't exceed 2⋅105 . Output For each test case, print one integer — the maximum number of segments that make a cool partition. Example InputCopy 8 6 1 2 2 3 1 5 8 1 2 1 3 2 1 3 2 5 5 4 3 2 1 10 5 8 7 5 8 5 7 8 10 9 3 1 2 2 9 3 3 1 4 3 2 4 1 2 6 4 5 4 5 6 4 8 1 2 1 2 1 2 1 2 OutputCopy 2 3 1 3 1 3 3 4 Note The first test case is explained in the statement. We can partition it into b1=[1,2] , b2=[2,3,1,5] . It can be shown there is no other partition with more segments. In the second test case, we can partition the array into b1=[1,2] , b2=[1,3,2] , b3=[1,3,2] . The maximum number of segments is 3 . In the third test case, the only partition we can make is b1=[5,4,3,2,1]
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06-09
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