Leetcode 554: Brick Wall
Given a rectangular wall made up of bricks with varying widths, your task is to determine the minimum number of bricks that a vertical line crosses. The line should be drawn such that it does not cross any brick’s edge, and you cannot place the line at the edges of the wall.
Problem
Approach
Steps
Complexity
Input: The input is a 2D array 'wall' where each row represents a row of bricks. Each brick in a row is represented by its width.
Example: Input: wall = [[2, 3, 1], [4, 2], [1, 3, 1], [3, 2, 1]]
Constraints:
• 1 <= n <= 104
• 1 <= wall[i].length <= 104
• 1 <= sum(wall[i].length) <= 2 * 104
• sum(wall[i]) is the same for each row i.
Output: The output should be the minimum number of bricks that a vertical line crosses.
Example: Output: 2
Constraints:
• The returned value should be an integer representing the minimum number of crossed bricks.
Goal: The goal is to find the vertical line position that crosses the fewest bricks.
Steps:
• For each row, calculate the position of the brick edges as you iterate through the row.
• Track the frequency of these positions across all rows using a map or hash table.
• The most frequent position indicates where the fewest bricks are crossed, and the answer is the number of rows minus the maximum frequency.
Goal: The input wall will have between 1 and 10^4 rows, and each row will have at least one brick with widths ranging from 1 to 2^31-1.
Steps:
• 1 <= wall.length <= 10^4
• 1 <= wall[i].length <= 10^4
• 1 <= sum(wall[i].length) <= 2 * 10^4
• sum(wall[i]) is the same for all rows.
Assumptions:
• The input wall will always have at least one row.
• The number of bricks in each row is guaranteed to be consistent in terms of total width.
• Input: Input: wall = [[2, 3, 1], [4, 2], [1, 3, 1], [3, 2, 1]]
• Explanation: The vertical line crossing the edge between the second and third bricks of the first row results in crossing only 2 bricks across all rows.
Approach: The approach involves tracking the positions of the edges of the bricks in each row and counting the frequency of these positions across all rows. The position that occurs most frequently is where the least number of bricks are crossed.
Observations:
• If the vertical line is placed at the edges where the most bricks align, fewer bricks will be crossed.
• We need to avoid crossing any edges of the bricks and aim for positions where the least number of bricks will be affected.
• This can be done efficiently by tracking the frequency of edge positions and selecting the one that minimizes the number of crossed bricks.
Steps:
• Initialize a map to store the frequency of edge positions.
• Iterate through each row and calculate the positions of the brick edges.
• Update the frequency map for each edge position.
• The answer is the number of rows minus the maximum frequency of any edge position.
Empty Inputs:
• The input will never be empty as the number of rows is guaranteed to be at least 1.
Large Inputs:
• The solution should efficiently handle up to 10^4 rows and total brick widths up to 2 * 10^4.
Special Values:
• If the wall has only one column, the vertical line will cross all bricks, and the answer is equal to the number of rows.
Constraints:
• The algorithm should work efficiently within the problem's constraints, particularly with large inputs.
int leastBricks(vector<vector<int>>& wall) {
unordered_map<int, int> edge_freq;
int max_freq = 0;
for(int row = 0; row < wall.size(); row++) {
int edge_pos = 0;
for(int brick_no = 0; brick_no < wall[row].size() - 1; brick_no++) {
int curr_brick_length = wall[row][brick_no];
edge_pos = edge_pos + curr_brick_length;
edge_freq[edge_pos]++;
max_freq = max(edge_freq[edge_pos], max_freq);
}
}
return wall.size() - max_freq;
}
1 : Function Definition
int leastBricks(vector<vector<int>>& wall) {
Defines the function `leastBricks`, which takes a 2D vector `wall` representing the brick wall and returns the minimum number of bricks that a vertical line intersects.
2 : Hash Map Initialization
unordered_map<int, int> edge_freq;
Initializes an unordered map `edge_freq` to store the frequency of each edge position encountered while iterating over the wall.
3 : Variable Initialization
int max_freq = 0;
Initializes a variable `max_freq` to track the highest frequency of any edge position encountered.
4 : Outer Loop (Row Traversal)
for(int row = 0; row < wall.size(); row++) {
Begins a loop to traverse each row of the wall.
5 : Edge Position Initialization
int edge_pos = 0;
Initializes `edge_pos` to keep track of the current edge position as we iterate through the bricks in a row.
6 : Inner Loop (Brick Traversal)
for(int brick_no = 0; brick_no < wall[row].size() - 1; brick_no++) {
Starts a loop to traverse each brick in the current row, excluding the last brick, to avoid counting the edge of the last brick.
7 : Brick Length Extraction
int curr_brick_length = wall[row][brick_no];
Extracts the length of the current brick in the row.
8 : Edge Position Update
edge_pos = edge_pos + curr_brick_length;
Updates the current edge position by adding the length of the current brick.
9 : Edge Frequency Update
edge_freq[edge_pos]++;
Increments the frequency count for the current edge position in the `edge_freq` map.
10 : Max Frequency Update
max_freq = max(edge_freq[edge_pos], max_freq);
Updates the `max_freq` variable to track the highest frequency of any edge position encountered so far.
11 : Return Statement
return wall.size() - max_freq;
Returns the minimum number of bricks intersected by a vertical line, which is the total number of rows minus the maximum frequency of edge positions.
Best Case: O(n)
Average Case: O(n)
Worst Case: O(n)
Description: The time complexity is linear with respect to the total number of bricks, as we are iterating through the entire wall once.
Best Case: O(n)
Worst Case: O(n)
Description: The space complexity is O(n) due to the storage required for the frequency map that tracks the edge positions.
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