Alice has n balloons arranged on a rope. You are given a 0-indexed string colors where colors[i] is the color of the ith balloon.
Alice wants the rope to be colorful. She does not want two consecutive balloons to be of the same color, so she asks Bob for help. Bob can remove some balloons from the rope to make it colorful. You are given a 0-indexed integer array neededTime where neededTime[i] is the time (in seconds) that Bob needs to remove the ith balloon from the rope.
Return the minimum time Bob needs to make the rope colorful.
Example 1:
Input: colors = "abaac", neededTime = [1,2,3,4,5] Output: 3 Explanation: In the above image, 'a' is blue, 'b' is red, and 'c' is green. Bob can remove the blue balloon at index 2. This takes 3 seconds. There are no longer two consecutive balloons of the same color. Total time = 3.
Example 2:
Input: colors = "abc", neededTime = [1,2,3] Output: 0 Explanation: The rope is already colorful. Bob does not need to remove any balloons from the rope.
Example 3:
Input: colors = "aabaa", neededTime = [1,2,3,4,1] Output: 2 Explanation: Bob will remove the balloons at indices 0 and 4. Each balloons takes 1 second to remove. There are no longer two consecutive balloons of the same color. Total time = 1 + 1 = 2.
Constraints:
n == colors.length == neededTime.length1 <= n <= 1051 <= neededTime[i] <= 104colors contains only lowercase English letters.This is a greedy technique using two pointers. Iterate over the string of balloon colors. For each sequence of consecutive balloons of the same color, use one pointer to find the maximum time required to remove a balloon (among those consecutive balloons). Accumulate the total removal time by subtracting this maximum time from the sum of all removal times for the sequence.
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Time Complexity: O(n), where n is the number of balloons. We iterate through the array once.
Space Complexity: O(1), no additional space is used other than a few variables.
This approach uses dynamic programming (DP) with state compression to minimize the time required to make all the balloons non-consecutive in terms of color. The solution leverages optimization by compressing the state to monitor the necessary reduction within nested loops over sequences of consecutive duplicates.
This C solution utilizes a dynamic programming array to store minimum times dynamically adjusted as pairs of consecutive balloons come into play. It keeps track of multiple states based on whether the current or previous balloons of the same color should be retained.
C++
Java
Python
C#
JavaScript
Time Complexity: O(n), for looping through the list.
Space Complexity: O(1), only using a couple of elements for the DP state transitions.
| Approach | Complexity |
|---|---|
| Two Pointer Approach | Time Complexity: O(n), where n is the number of balloons. We iterate through the array once. |
| Dynamic Programming with State Compression | Time Complexity: O(n), for looping through the list. |
Minimum Time To Make Rope Colorful - Leetcode 1578 - Python • NeetCodeIO • 17,351 views views
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