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2555. Maximize Win From Two Segments
Description
There are some prizes on the X-axis. You are given an integer array prizePositions
that is sorted in non-decreasing order, where prizePositions[i]
is the position of the ith
prize. There could be different prizes at the same position on the line. You are also given an integer k
.
You are allowed to select two segments with integer endpoints. The length of each segment must be k
. You will collect all prizes whose position falls within at least one of the two selected segments (including the endpoints of the segments). The two selected segments may intersect.
- For example if
k = 2
, you can choose segments[1, 3]
and[2, 4]
, and you will win any prize i that satisfies1 <= prizePositions[i] <= 3
or2 <= prizePositions[i] <= 4
.
Return the maximum number of prizes you can win if you choose the two segments optimally.
Example 1:
Input: prizePositions = [1,1,2,2,3,3,5], k = 2 Output: 7 Explanation: In this example, you can win all 7 prizes by selecting two segments [1, 3] and [3, 5].
Example 2:
Input: prizePositions = [1,2,3,4], k = 0 Output: 2 Explanation: For this example, one choice for the segments is[3, 3]
and[4, 4],
and you will be able to get2
prizes.
Constraints:
1 <= prizePositions.length <= 105
1 <= prizePositions[i] <= 109
0 <= k <= 109
prizePositions
is sorted in non-decreasing order.
Solutions
Solution 1: Dynamic Programming + Binary Search
We define $f[i]$ as the maximum number of prizes that can be obtained by selecting a segment of length $k$ from the first $i$ prizes. Initially, $f[0] = 0$. We define the answer variable as $ans = 0$.
Next, we enumerate the position $x$ of each prize, and use binary search to find the leftmost prize index $j$ such that $prizePositions[j] \geq x - k$. At this point, we update the answer $ans = \max(ans, f[j] + i - j)$, and update $f[i] = \max(f[i - 1], i - j)$.
Finally, we return $ans$.
The time complexity is $O(n \times \log n)$, and the space complexity is $O(n)$. Where $n$ is the number of prizes.
-
class Solution { public int maximizeWin(int[] prizePositions, int k) { int n = prizePositions.length; int[] f = new int[n + 1]; int ans = 0; for (int i = 1; i <= n; ++i) { int x = prizePositions[i - 1]; int j = search(prizePositions, x - k); ans = Math.max(ans, f[j] + i - j); f[i] = Math.max(f[i - 1], i - j); } return ans; } private int search(int[] nums, int x) { int left = 0, right = nums.length; while (left < right) { int mid = (left + right) >> 1; if (nums[mid] >= x) { right = mid; } else { left = mid + 1; } } return left; } }
-
class Solution { public: int maximizeWin(vector<int>& prizePositions, int k) { int n = prizePositions.size(); vector<int> f(n + 1); int ans = 0; for (int i = 1; i <= n; ++i) { int x = prizePositions[i - 1]; int j = lower_bound(prizePositions.begin(), prizePositions.end(), x - k) - prizePositions.begin(); ans = max(ans, f[j] + i - j); f[i] = max(f[i - 1], i - j); } return ans; } };
-
class Solution: def maximizeWin(self, prizePositions: List[int], k: int) -> int: n = len(prizePositions) f = [0] * (n + 1) ans = 0 for i, x in enumerate(prizePositions, 1): j = bisect_left(prizePositions, x - k) ans = max(ans, f[j] + i - j) f[i] = max(f[i - 1], i - j) return ans
-
func maximizeWin(prizePositions []int, k int) (ans int) { n := len(prizePositions) f := make([]int, n+1) for i, x := range prizePositions { j := sort.Search(n, func(h int) bool { return prizePositions[h] >= x-k }) ans = max(ans, f[j]+i-j+1) f[i+1] = max(f[i], i-j+1) } return }
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function maximizeWin(prizePositions: number[], k: number): number { const n = prizePositions.length; const f: number[] = Array(n + 1).fill(0); let ans = 0; const search = (x: number): number => { let left = 0; let right = n; while (left < right) { const mid = (left + right) >> 1; if (prizePositions[mid] >= x) { right = mid; } else { left = mid + 1; } } return left; }; for (let i = 1; i <= n; ++i) { const x = prizePositions[i - 1]; const j = search(x - k); ans = Math.max(ans, f[j] + i - j); f[i] = Math.max(f[i - 1], i - j); } return ans; }