Unguarded Cells: grid, hash and a linear approach

The problem this weekend asks for the number of cells that are not guarded. Since the limits of the grid are in the 10^5 range, we're then looking for a O(N) solution.
First, it would be wise to add the positions of the guards and the walls in handy hash-tables. Relatively simple.
After that, think this way: if you scan the grid in a left-to-right analyzing each row, you can increment the cells that are not reached by a guard in that row from left to right. Any cell that has a 1 at the end of this operation is free from guards in that row from left to right.
Now apply the same approach in the other 3 directions: right to left, top down and bottoms-up. By doing so, at the very end, any cell that reaches the number 4 is free from any guard. And that's your answer.
Thus, this would be a 4*m*n, and since m*n<=10^5 (as per the constraint), then the solution becomes O(4*10^5), which is very tractable and considered linear in this case. Code is down below, cheers, ACC.


2257. Count Unguarded Cells in the Grid
Medium

You are given two integers m and n representing a 0-indexed m x n grid. You are also given two 2D integer arrays guards and walls where guards[i] = [rowi, coli] and walls[j] = [rowj, colj] represent the positions of the ith guard and jth wall respectively.

A guard can see every cell in the four cardinal directions (north, east, south, or west) starting from their position unless obstructed by a wall or another guard. A cell is guarded if there is at least one guard that can see it.

Return the number of unoccupied cells that are not guarded.

Example 1:

Input: m = 4, n = 6, guards = [[0,0],[1,1],[2,3]], walls = [[0,1],[2,2],[1,4]]
Output: 7
Explanation: The guarded and unguarded cells are shown in red and green respectively in the above diagram.
There are a total of 7 unguarded cells, so we return 7.

Example 2:

Input: m = 3, n = 3, guards = [[1,1]], walls = [[0,1],[1,0],[2,1],[1,2]]
Output: 4
Explanation: The unguarded cells are shown in green in the above diagram.
There are a total of 4 unguarded cells, so we return 4.

Constraints:

  • 1 <= m, n <= 105
  • 2 <= m * n <= 105
  • 1 <= guards.length, walls.length <= 5 * 104
  • 2 <= guards.length + walls.length <= m * n
  • guards[i].length == walls[j].length == 2
  • 0 <= rowi, rowj < m
  • 0 <= coli, colj < n
  • All the positions in guards and walls are unique.

public int CountUnguarded(int m, int n, int[][] guards, int[][] walls)
{
 int[][] count = new int[m][];
 for (int i = 0; i < count.Length; i++) count[i] = new int[n]; Hashtable guardsHash = new Hashtable(); for (int i = 0; i < guards.Length; i++) { long key = guards[i][0] * (100000 + 5) + guards[i][1]; guardsHash.Add(key, true); } Hashtable wallsHash = new Hashtable(); for (int i = 0; i < walls.Length; i++) { long key = walls[i][0] * (100000 + 5) + walls[i][1]; wallsHash.Add(key, true); } //L->R
 for (int r = 0; r < m; r++) { bool lastIsGuard = false; for (int c = 0; c < n; c++) { long key = r * (100000 + 5) + c; if (guardsHash.ContainsKey(key)) { lastIsGuard = true; } else if (wallsHash.ContainsKey(key)) { lastIsGuard = false; } else if (!lastIsGuard) { count[r][c]++; } } } //R->L
 for (int r = 0; r < m; r++) { bool lastIsGuard = false; for (int c = n - 1; c>= 0; c--)
 {
 long key = r * (100000 + 5) + c;
 if (guardsHash.ContainsKey(key))
 {
 lastIsGuard = true;
 }
 else if (wallsHash.ContainsKey(key))
 {
 lastIsGuard = false;
 }
 else if (!lastIsGuard)
 {
 count[r][c]++;
 }
 }
 }
 //T->B
 for (int c = 0; c < n; c++) { bool lastIsGuard = false; for (int r = 0; r < m; r++) { long key = r * (100000 + 5) + c; if (guardsHash.ContainsKey(key)) { lastIsGuard = true; } else if (wallsHash.ContainsKey(key)) { lastIsGuard = false; } else if (!lastIsGuard) { count[r][c]++; } } } //B->T
 int retVal = 0;
 for (int c = 0; c < n; c++) { bool lastIsGuard = false; for (int r = m - 1; r>= 0; r--)
 {
 long key = r * (100000 + 5) + c;
 if (guardsHash.ContainsKey(key))
 {
 lastIsGuard = true;
 }
 else if (wallsHash.ContainsKey(key))
 {
 lastIsGuard = false;
 }
 else if (!lastIsGuard)
 {
 count[r][c]++;
 if (count[r][c] == 4) retVal++;
 }
 }
 }
 return retVal;
}

Comments

Post a Comment

[フレーム]

Popular posts from this blog

Quasi FSM (Finite State Machine) problem + Vibe

Not really an FSM problem since the state isn't changing, it is just defined by the current input. Simply following the instructions should do it. Using VSCode IDE you can also engage the help of Cline or Copilot for a combo of coding and vibe coding, see below screenshot. Cheers, ACC. Process String with Special Operations I - LeetCode You are given a string  s  consisting of lowercase English letters and the special characters:  * ,  # , and  % . Build a new string  result  by processing  s  according to the following rules from left to right: If the letter is a  lowercase  English letter append it to  result . A  '*'   removes  the last character from  result , if it exists. A  '#'   duplicates  the current  result  and  appends  it to itself. A  '%'   reverses  the current  result . Return the final string  result  after processing all char...

Shortest Bridge – A BFS Story (with a Twist)

Here's another one from the Google 30 Days challenge on LeetCode — 934. Shortest Bridge . The goal? Given a 2D binary grid where two islands (groups of 1s) are separated by water (0s), flip the fewest number of 0s to 1s to connect them. Easy to describe. Sneaky to implement well. 🧭 My Approach My solution follows a two-phase Breadth-First Search (BFS) strategy: Find and mark one island : I start by scanning the grid until I find the first 1 , then use BFS to mark all connected land cells as 2 . I store their positions for later use. Bridge-building BFS : For each cell in the marked island, I run a BFS looking for the second island. Each BFS stops as soon as it hits a cell with value 1 . The minimum distance across all these searches gives the shortest bridge. πŸ” Code Snippet Here's the core logic simplified: public int ShortestBridge(int[][] grid) { // 1. Mark one island as '2' and gather its coordinates List<int> island = FindAndMark...

Classic Dynamic Programming IX

A bit of vibe code together with OpenAI O3. I asked O3 to just generate the sieve due to laziness. Sieve is used to calculate the first M primes (when I was using Miller-Rabin, was giving me TLE). The DP follows from that in a straightforward way: calculate the numbers from i..n-1, then n follows by calculating the min over all M primes. Notice that I made use of Goldbach's Conjecture as a way to optimize the code too. Goldbach's Conjecture estates that any even number greater than 2 is the sum of 2 primes. The conjecture is applied in the highlighted line. Cheers, ACC. PS: the prompt for the sieve was the following, again using Open AI O3 Advanced Reasoning: " give me a sieve to find the first M prime numbers in C#. The code should produce a List<int> with the first M primes " Minimum Number of Primes to Sum to Target - LeetCode You are given two integers  n  and  m . You have to select a multiset of  prime numbers  from the  first   m  pri...