Can anybody explain me how to solve E using binnary search(I can`t understand editorial)
№ | Пользователь | Рейтинг |
---|---|---|
1 | tourist | 3993 |
2 | jiangly | 3743 |
3 | orzdevinwang | 3707 |
4 | Radewoosh | 3627 |
5 | jqdai0815 | 3620 |
6 | Benq | 3564 |
7 | Kevin114514 | 3443 |
8 | ksun48 | 3434 |
9 | Rewinding | 3397 |
10 | Um_nik | 3396 |
Страны | Города | Организации | Всё → |
№ | Пользователь | Вклад |
---|---|---|
1 | cry | 167 |
2 | Um_nik | 163 |
3 | maomao90 | 162 |
3 | atcoder_official | 162 |
5 | adamant | 159 |
6 | -is-this-fft- | 158 |
7 | awoo | 155 |
8 | TheScrasse | 154 |
9 | Dominater069 | 153 |
10 | djm03178 | 152 |
Название |
---|
Note: I use 1-indexing and a translator.
Idea: let's go through all possible subarrays [i..j], and if sum of elements is equal to s, then recalculate the answer: ans = min(ans, i — 1 + n — j) — that is, we need to remove (i — 1) elements from the beginning and (n — j) from the end.
This is O(n^2), we can improve with binary search:
Let's count the prefix sums in the array a, and go through j. Then we need to find the leftmost i so that (a[j] — a[i — 1]) == s, in other words, find the leftmost (a[j] — s) in the prefix-sum array. Then the answer is recalculated in the same way as in the case of O(n^2).
Now O(n log n).
My solution: link
Why downvotes? I only help with solution!
thanks very much :) You realy help me bro)