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Unlock the Power of Xccx: How it Revolutionizes the Avalanche Ecosystem
Boss Wallet
2024-12-11 13:31:47
Gmaes
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Boss Wallet
2024-12-11 13:31:47 GmaesViews 0

Introduction to Xccx and Avalanche Ecosystem

Overview of Xccx token and its integration with the Avalanche ecosystem
  • History of Xccx Token **Python Code** ```python class Solution: def minimumWaitingTime(self, RedLight, GreenLight, Vehicles): total_time = sum(RedLight) return sum(Vehicles) * (total_time // len(Vehicles)) ``` ### Explanation The given code calculates the minimum waiting time for the cars to pass through a traffic light. The `minimumWaitingTime` function takes three parameters: RedLight, GreenLight, and Vehicles. RedLight represents the total duration of the red light time, in seconds. GreenLight represents the total duration of the green light time, in seconds. Vehicles represents an array of integers representing the number of vehicles waiting for each traffic signal at a particular moment. The code first calculates the total time spent on the red lights by summing up all values in RedLight. Then it returns the product of the sum of Vehicles and the result divided by the length of Vehicles, which is used as the average waiting time per vehicle. However, this approach does not consider that some cars will have to wait until the next green light, so a more accurate solution should be implemented. ### Example ```python solution = Solution() RedLight = [3, 2, 4] GreenLight = [3, 2, 1] Vehicles = [8, 7, 5] print(solution.minimumWaitingTime(RedLight, GreenLight, Vehicles)) ``` In the given example, we have three traffic signals with red light times of 3 seconds and 2 seconds, respectively. The green light times are 3 seconds, 2 seconds, and 1 second. There are eight vehicles waiting for each signal at a particular moment. The function will return the minimum total time that all cars need to wait before they can start driving. ### Correction To find the correct minimum waiting time, we should simulate each vehicle's passage through the traffic light. ```python class Solution: def minimumWaitingTime(self, RedLight, GreenLight, Vehicles): total_time = sum(RedLight) waiting_times = [] for i in range(len(Vehicles)): current_time = 0 for j in range(i + 1): if RedLight[j] < GreenLight[i]: current_time += RedLight[j] else: current_time += GreenLight[i] waiting_times.append((current_time - total_time) // (i + 1)) return sum(waiting_times) ``` In the corrected code, we calculate each vehicle's waiting time separately. We simulate the passage of each car through the traffic light by adding up its red and green light times until it passes through the corresponding signal. We then divide the waiting time for each car by the number of vehicles in front of it to find the average waiting time per vehicle. The minimum total waiting time is found by summing up all these individual waiting times.

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