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Java-based LeetCode algorithm problem solutions, regularly updated
package g1601_1700.s1673_find_the_most_competitive_subsequence;
// #Medium #Array #Greedy #Stack #Monotonic_Stack
// #2022_04_19_Time_7_ms_(96.82%)_Space_54.9_MB_(88.07%)
/**
* 1673 - Find the Most Competitive Subsequence\.
*
* Medium
*
* Given an integer array `nums` and a positive integer `k`, return _the most **competitive** subsequence of_ `nums` _of size_ `k`.
*
* An array's subsequence is a resulting sequence obtained by erasing some (possibly zero) elements from the array.
*
* We define that a subsequence `a` is more **competitive** than a subsequence `b` (of the same length) if in the first position where `a` and `b` differ, subsequence `a` has a number **less** than the corresponding number in `b`. For example, `[1,3,4]` is more competitive than `[1,3,5]` because the first position they differ is at the final number, and `4` is less than `5`.
*
* **Example 1:**
*
* **Input:** nums = [3,5,2,6], k = 2
*
* **Output:** [2,6]
*
* **Explanation:** Among the set of every possible subsequence: {[3,5], [3,2], [3,6], [5,2], [5,6], [2,6]}, [2,6] is the most competitive.
*
* **Example 2:**
*
* **Input:** nums = [2,4,3,3,5,4,9,6], k = 4
*
* **Output:** [2,3,3,4]
*
* **Constraints:**
*
* * 1 <= nums.length <= 105
* * 0 <= nums[i] <= 109
* * `1 <= k <= nums.length`
**/
public class Solution {
public int[] mostCompetitive(int[] nums, int k) {
int[] r = new int[k];
int n = nums.length;
int j = 0;
for (int i = 0; i < n; i++) {
if (i == 0) {
r[j] = nums[i];
j++;
} else {
int l = j - 1;
while ((l >= 0) && (nums[i] < r[l]) && ((n - i) >= (k - l))) {
l--;
}
j = l + 1;
if (j < k) {
r[j] = nums[i];
j++;
}
}
}
return r;
}
}
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