In a mystic dungeon, n magicians are standing in a line. Each magician has an attribute that gives you energy. Some magicians can give you negative energy, which means taking energy from you.
You have been cursed in such a way that after absorbing energy from magician i, you will be instantly transported to magician (i + k). This process will be repeated until you reach the magician where (i + k) does not exist.
In other words, you will choose a starting point and then teleport with k jumps until you reach the end of the magicians' sequence, absorbing all the energy during the journey.
You are given an array energy and an integer k. Return the maximum possible energy you can gain.
Example 1:
Input: energy = [5,2,-10,-5,1], k = 3
Output: 3
Explanation: We can gain a total energy of 3 by starting from magician 1 absorbing 2 + 1 = 3.
Example 2:
Input: energy = [-2,-3,-1], k = 2
Output: -1
Explanation: We can gain a total energy of -1 by starting from magician 2.
Constraints:
1 <= energy.length <= 105-1000 <= energy[i] <= 10001 <= k <= energy.length - 1
The brute force approach involves iterating over all possible solutions and checking which one satisfies the condition of the problem. This might not be optimal in terms of efficiency but is straightforward to implement.
solve function implements the brute force solution by iterating through possible combinations and checking each for the needed condition.
C++
Java
Python
C#
JavaScript
Time Complexity: O(n^2)
Space Complexity: O(1)
This approach leverages hash maps (or dictionaries) to achieve a more efficient solution. By storing already computed combinations, we reduce the number of operations significantly compared to brute force.
The function solve would use a hash map to track and compute results efficiently, significantly reducing the number of redundant calculations.
C++
Java
Python
C#
JavaScript
Time Complexity: O(n)
Space Complexity: O(n)
| Approach | Complexity |
|---|---|
| Brute Force Approach | Time Complexity: O(n^2) |
| Optimized Approach Using Hash Map | Time Complexity: O(n) |
The unfair way I got good at Leetcode • Dave Burji • 596,394 views views
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