Zombie Clusters Hackerrank Solution
Zombie clusters is a problem from Hackerrank, a platform for practicing and improving coding skills. The problem statement is as follows:
Zombie Clusters Hackerrank Solution
Zombie Clusters Hackerrank Solution
Zombie clusters is a problem from Hackerrank, a platform for practicing and improving coding skills. The problem statement is as follows:
Zombie Clusters Hackerrank Solution
A zombie cluster is a group of zombies who are directly or indirectly linked to each other by some means. For example, if zombie 0 knows zombie 1 and zombie 1 knows zombie 2, then zombies 0, 1, and 2 are in the same cluster. A zombie can also be in a cluster by itself. You are given a list of zombies as an n x n matrix, where n is the number of zombies in the city. Each row represents a zombie, and each column represents who they know. If the value at row i and column j is 1, then zombie i knows zombie j. Note that knowing is a symmetric relation: if zombie i knows zombie j, then zombie j knows zombie i. Your task is to find the number of zombie clusters in the city.
To solve this problem, we can use a depth-first search (DFS) algorithm to traverse the matrix and mark the visited zombies. Whenever we encounter a new unvisited zombie, we start a new DFS from that zombie and increment the cluster count by one. We repeat this process until we have visited all the zombies in the matrix. Here is a possible Python solution using DFS:
def zombieCluster(zombies): # Initialize the cluster count and the visited set count = 0 visited = set() # Define a helper function for DFS def dfs(i): # Mark the current zombie as visited visited.add(i) # Loop through all the zombies that the current zombie knows for j in range(len(zombies)): # If the current zombie knows another zombie and that zombie is not visited if zombies[i][j] == '1' and j not in visited: # Recursively call DFS on that zombie dfs(j) # Loop through all the zombies in the matrix for i in range(len(zombies)): # If the current zombie is not visited if i not in visited: # Start a new DFS from that zombie and increment the cluster count by one dfs(i) count += 1 # Return the cluster count return count
This solution has a time complexity of O(n^2), where n is the number of zombies, and a space complexity of O(n), where n is the number of zombies. You can find more details and test cases for this problem on Hackerrank .
Here are some additional points that you can include in your article:
The problem of zombie clusters can be seen as a graph problem, where each zombie is a node and each connection is an edge. The number of zombie clusters is then equivalent to the number of connected components in the graph.
There are other ways to solve this problem besides DFS, such as breadth-first search (BFS), union-find, or matrix multiplication. Each method has its own advantages and disadvantages in terms of time and space complexity, readability, and scalability.
You can also compare and contrast the zombie clusters problem with other similar problems, such as finding the number of islands in a grid, or the number of friends circles in a social network.
I hope this helps you write your article. If you need more assistance, please let me know. ?
Here are some additional points that you can include in your article: - The problem of zombie clusters can be seen as a graph problem, where each zombie is a node and each connection is an edge. The number of zombie clusters is then equivalent to the number of connected components in the graph. - There are other ways to solve this problem besides DFS, such as breadth-first search (BFS), union-find, or matrix multiplication. Each method has its own advantages and disadvantages in terms of time and space complexity, readability, and scalability. - You can also compare and contrast the zombie clusters problem with other similar problems, such as finding the number of islands in a grid, or the number of friends circles in a social network. I hope this helps you write your article. If you need more assistance, please let me know. ?
Here are some more points that you can include in your article:
You can also explain the intuition and the implementation of the DFS algorithm in more detail, such as how it uses a stack or recursion to explore the matrix, and how it marks the visited zombies using a set or a boolean array.
You can also provide some examples of input and output for the zombie clusters problem, and show how the DFS algorithm works step by step on these examples. You can use tables or diagrams to illustrate the process.
You can also discuss some of the challenges and limitations of the zombie clusters problem, such as how it assumes that knowing is a symmetric and transitive relation, and how it does not account for the possibility of zombies changing their connections over time.
I hope this helps you write your article. If you need more assistance, please let me know. ?
Here are some more points that you can include in your article:
You can also explain the intuition and the implementation of the DFS algorithm in more detail, such as how it uses a stack or recursion to explore the matrix, and how it marks the visited zombies using a set or a boolean array.
You can also provide some examples of input and output for the zombie clusters problem, and show how the DFS algorithm works step by step on these examples. You can use tables or diagrams to illustrate the process.
You can also discuss some of the challenges and limitations of the zombie clusters problem, such as how it assumes that knowing is a symmetric and transitive relation, and how it does not account for the possibility of zombies changing their connections over time.
I hope this helps you write your article. If you need more assistance, please let me know. ?
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