373. Find K Pairs with Smallest Sums

https://leetcode.com/problems/find-k-pairs-with-smallest-sums/

You are given two integer arrays nums1 and nums2 sorted in ascending order and an integer k.

Define a pair (u,v) which consists of one element from the first array and one element from the second array.

Find the k pairs (u1,v1),(u2,v2) ...(uk,vk) with the smallest sums.

Example 1:

Input: nums1 = [1,7,11], nums2 = [2,4,6], k = 3
Output: [[1,2],[1,4],[1,6]] 
Explanation: The first 3 pairs are returned from the sequence: 
             [1,2],[1,4],[1,6],[7,2],[7,4],[11,2],[7,6],[11,4],[11,6]

Example 2:

Input: nums1 = [1,1,2], nums2 = [1,2,3], k = 2
Output: [1,1],[1,1]
Explanation: The first 2 pairs are returned from the sequence: 
             [1,1],[1,1],[1,2],[2,1],[1,2],[2,2],[1,3],[1,3],[2,3]

Example 3:

Input: nums1 = [1,2], nums2 = [3], k = 3
Output: [1,3],[2,3]
Explanation: All possible pairs are returned from the sequence: [1,3],[2,3]

Thoughts

两个排好序的数组，从两个数组中分别选一个元素组成pair，返回前K个和最小的pair。思路类似ugly number。维持min heap，初始时先放入K个candidates，对于任意nums1[0:K-1]内元素，把与它搭配最小的nums2[0]放入。当把pair (nums1[i], nums2[j])从pq抛出并计入res后，nums1将它的下一个candidate(nums1[i], nums2[j +1])放入pq。

Code

from heapq import heappop, heappush

class Solution:
    def kSmallestPairs(self, nums1: List[int], nums2: List[int], k: int) -> List[List[int]]:
        res, q = [], []
        if len(nums1) == 0 or len(nums2) == 0 or k == 0:
            return res
        for i in range(k):
            if i >= len(nums1):
                break
            heappush(q, (nums1[i] + nums2[0], nums1[i], 0))
        while k and q:
            cur = heappop(q)
            res.append([cur[1], cur[0] - cur[1]])
            k -= 1
            if cur[2] == len(nums2) - 1:
                continue
            heappush(q, (cur[1] + nums2[cur[2] + 1], cur[1], cur[2] + 1))
            
        return res
            

class Solution {
    public List<int[]> kSmallestPairs(int[] nums1, int[] nums2, int k) {
        PriorityQueue<int[]> pq = new PriorityQueue<>((a, b) -> a[0] + a[1] - b[0] - b[1]);
        List<int[]> res = new ArrayList<>();
        if (nums1.length == 0 || nums2.length == 0 || k == 0) {
            return res;
        }
        for (int i = 0; i < nums1.length; i++) {
            // 可能最小值的candidates, 和当前指向nums2的位置
            pq.offer(new int[]{nums1[i], nums2[0], 0});
        }

        for (int i = 0; i < k && !pq.isEmpty(); i++) {
            int[] min = pq.poll();
            res.add(new int[]{min[0], min[1]});
            if (min[2] == nums2.length - 1) {
                continue;
            }
            // 每次弹出一个就把它指向的下一个当作候选放入pq
            pq.offer(new int[]{min[0], nums2[min[2] + 1], min[2] + 1});
        }
        return res;
    }
}

Analysis

时间复杂度O(klogn)

有没有办法可以优化呢？还可以，当k<n时，我们实际上可以只初始化size为k的heap，因为nums1中排在k之后永远不会用到, 因为即使nums2中次大永远不被选到，k个都是在更换pair中的nums1，那最多也就到k，不会到nums1中k之后的。所以时间复杂度O(klgk).