Need help with algorithm
PLEASE HELP ME
Problem Statement
You are given an array of integers. You need to implement a data structure that supports the following operations in O(log n) time:
Range Sum [L, R] (0‑indexed). Return the sum of all elements in the subarray from index L to R inclusive.
Insert element x at position pos. After insertion, x must be located at index pos. (Constraints: |x| ≤ 3⋅10^4, 0 ≤ pos ≤ current array size).
Delete element at position pos. (Constraints: 0 ≤ pos < current array size).
Assign value x to all elements in [L, R]. (Constraints: |x| ≤ 3⋅10^4, 0 ≤ L ≤ R < current array size).
Add value x to all elements in [L, R]. (Constraints: |x| ≤ 3⋅10^4, 0 ≤ L ≤ R < current array size).
Apply next_permutation to subarray [L, R]. Works exactly like the STL algorithm:
Example: next_permutation([4,3,2,1]) = [1,2,3,4].
Apply prev_permutation to subarray [L, R]. Works exactly like the STL algorithm:
Example: prev_permutation([1,2,2,2,3,3,4]) = [4,3,3,2,2,2,1].
It is guaranteed that all queries are valid with respect to the current array size.
Input Format
First line: integer n (1 ≤ n ≤ 3⋅10^4) — the number of elements in the array.
Second line: n integers (each |a[i]| ≤ 3⋅10^4) — the initial array.
Third line: integer q (1 ≤ q ≤ 10^5) — the number of queries.
Next q lines: each line contains one query in one of the formats described above.
Output Format
For each query of type 1 (range sum), output the result on a separate line.
After processing all queries, output the final state of the array in one line.
Example
Input
7
1 2 3 4 5 6 7
8
4 5 1 3
2 3 3
5 2 0 4
7 0 6
6 0 3
3 2
1 1 5
1 0 6
Output
28
40
5 3 7 6 7 5 7
I can't solve this problem, and for some reason, no neural network can help me. I have my own code, but it doesn't work on the 5th test, and it displays a limited time issue.
I can't solve this
Problem Statement
You are given an array of integers. You need to implement a data structure that supports the following operations in O(log n) time:
Range Sum [L, R] (0‑indexed). Return the sum of all elements in the subarray from index L to R inclusive.
Insert element x at position pos. After insertion, x must be located at index pos. (Constraints: |x| ≤ 3⋅10^4, 0 ≤ pos ≤ current array size).
Delete element at position pos. (Constraints: 0 ≤ pos < current array size).
Assign value x to all elements in [L, R]. (Constraints: |x| ≤ 3⋅10^4, 0 ≤ L ≤ R < current array size).
Add value x to all elements in [L, R]. (Constraints: |x| ≤ 3⋅10^4, 0 ≤ L ≤ R < current array size).
Apply next_permutation to subarray [L, R]. Works exactly like the STL algorithm:
Example: next_permutation([4,3,2,1]) = [1,2,3,4].
Apply prev_permutation to subarray [L, R]. Works exactly like the STL algorithm:
Example: prev_permutation([1,2,2,2,3,3,4]) = [4,3,3,2,2,2,1].
It is guaranteed that all queries are valid with respect to the current array size.
Input Format
First line: integer n (1 ≤ n ≤ 3⋅10^4) — the number of elements in the array.
Second line: n integers (each |a[i]| ≤ 3⋅10^4) — the initial array.
Third line: integer q (1 ≤ q ≤ 10^5) — the number of queries.
Next q lines: each line contains one query in one of the formats described above.
Output Format
For each query of type 1 (range sum), output the result on a separate line.
After processing all queries, output the final state of the array in one line.
Example
Input
7
1 2 3 4 5 6 7
8
4 5 1 3
2 3 3
5 2 0 4
7 0 6
6 0 3
3 2
1 1 5
1 0 6
Output
28
40
5 3 7 6 7 5 7
I can't solve this problem, and for some reason, no neural network can help me. I have my own code, but it doesn't work on the 5th test, and it displays a limited time issue.
I can't solve this
