2386. Find the K-Sum of an Array

Description

You are given an integer array nums and a positive integer k. You can choose any subsequence of the array and sum all of its elements together.

We define the K-Sum of the array as the k^th largest subsequence sum that can be obtained (not necessarily distinct).

Return the K-Sum of the array.

A subsequence is an array that can be derived from another array by deleting some or no elements without changing the order of the remaining elements.

Note that the empty subsequence is considered to have a sum of 0.

Example 1:

Input: nums = [2,4,-2], k = 5
Output: 2
Explanation: All the possible subsequence sums that we can obtain are the following sorted in decreasing order:
- 6, 4, 4, 2, 2, 0, 0, -2.
The 5-Sum of the array is 2.

Example 2:

Input: nums = [1,-2,3,4,-10,12], k = 16
Output: 10
Explanation: The 16-Sum of the array is 10.

Constraints:

n == nums.length
1 <= n <= 10⁵
-10⁹ <= nums[i] <= 10⁹
1 <= k <= min(2000, 2ⁿ)

Solutions

Solution 1: Priority Queue (Min Heap)

First, we find the maximum subsequence sum $mx$, which is the sum of all positive numbers.

It can be found that the sum of other subsequences can be regarded as the maximum subsequence sum, minus the sum of other part of the subsequence. Therefore, we can convert the problem into finding the $k$-th smallest subsequence sum.

We only need to sort all numbers in ascending order by their absolute values, then establish a min heap, storing pairs $(s, i)$, representing the current sum is $s$, and the index of the next number to be selected is $i$.

Each time we take out the top of the heap, and put in two new situations: one is to select the next position, and the other is to select the next position and not select this position.

Since the array is sorted from small to large, this method can traverse all subsequence sums in order without duplication.

The time complexity is $O(n \times \log n + k \times \log k)$, where $n$ is the length of the array nums, and $k$ is the given $k$ in the problem.

Python3JavaC++Go

class Solution:
    def kSum(self, nums: List[int], k: int) -> int:
        mx = 0
        for i, x in enumerate(nums):
            if x > 0:
                mx += x
            else:
                nums[i] = -x
        nums.sort()
        h = [(0, 0)]
        for _ in range(k - 1):
            s, i = heappop(h)
            if i < len(nums):
                heappush(h, (s + nums[i], i + 1))
                if i:
                    heappush(h, (s + nums[i] - nums[i - 1], i + 1))
        return mx - h[0][0]

class Solution {
    public long kSum(int[] nums, int k) {
        long mx = 0;
        int n = nums.length;
        for (int i = 0; i < n; ++i) {
            if (nums[i] > 0) {
                mx += nums[i];
            } else {
                nums[i] *= -1;
            }
        }
        Arrays.sort(nums);
        PriorityQueue<Pair<Long, Integer>> pq
            = new PriorityQueue<>(Comparator.comparing(Pair::getKey));
        pq.offer(new Pair<>(0L, 0));
        while (--k > 0) {
            var p = pq.poll();
            long s = p.getKey();
            int i = p.getValue();
            if (i < n) {
                pq.offer(new Pair<>(s + nums[i], i + 1));
                if (i > 0) {
                    pq.offer(new Pair<>(s + nums[i] - nums[i - 1], i + 1));
                }
            }
        }
        return mx - pq.peek().getKey();
    }
}

class Solution {
public:
    long long kSum(vector<int>& nums, int k) {
        long long mx = 0;
        int n = nums.size();
        for (int i = 0; i < n; ++i) {
            if (nums[i] > 0) {
                mx += nums[i];
            } else {
                nums[i] *= -1;
            }
        }
        sort(nums.begin(), nums.end());
        using pli = pair<long long, int>;
        priority_queue<pli, vector<pli>, greater<pli>> pq;
        pq.push({0, 0});
        while (--k) {
            auto p = pq.top();
            pq.pop();
            long long s = p.first;
            int i = p.second;
            if (i < n) {
                pq.push({s + nums[i], i + 1});
                if (i) {
                    pq.push({s + nums[i] - nums[i - 1], i + 1});
                }
            }
        }
        return mx - pq.top().first;
    }
};

func kSum(nums []int, k int) int64 {
    mx := 0
    for i, x := range nums {
        if x > 0 {
            mx += x
        } else {
            nums[i] *= -1
        }
    }
    sort.Ints(nums)
    h := &hp{{0, 0}}
    for k > 1 {
        k--
        p := heap.Pop(h).(pair)
        if p.i < len(nums) {
            heap.Push(h, pair{p.sum + nums[p.i], p.i + 1})
            if p.i > 0 {
                heap.Push(h, pair{p.sum + nums[p.i] - nums[p.i-1], p.i + 1})
            }
        }
    }
    return int64(mx) - int64((*h)[0].sum)
}

type pair struct{ sum, i int }
type hp []pair

func (h hp) Len() int           { return len(h) }
func (h hp) Less(i, j int) bool { return h[i].sum < h[j].sum }
func (h hp) Swap(i, j int)      { h[i], h[j] = h[j], h[i] }
func (h *hp) Push(v any)        { *h = append(*h, v.(pair)) }
func (h *hp) Pop() any          { a := *h; v := a[len(a)-1]; *h = a[:len(a)-1]; return v }

2386. Find the K-Sum of an Array

Description

Solutions

Solution 1: Priority Queue (Min Heap)

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