
Problem Statement
In computational problems involving matrices, a row-sorted binary matrix is a common type, where each row consists only of 0
s and 1
s, sorted in non-decreasing order (i.e., all 0
s come before any 1
s in a row). Given such a binary matrix, which you cannot access directly except through a provided interface BinaryMatrix
, the challenge is to find the index of the leftmost column that contains at least one 1
.
The BinaryMatrix
interface offers:
BinaryMatrix.get(row, col)
: Fetches the element at the specified row and column.BinaryMatrix.dimensions()
: Returns the dimensions of the matrix as a two-element list[rows, cols]
.
Constraints include a limit of 1000 calls to BinaryMatrix.get
to avoid brute force approaches. If no column with a 1
is found, the function should return -1
.
Examples
Example 1
Input:
mat = [[0,0],[1,1]]
Output:
0
Example 2
Input:
mat = [[0,0],[0,1]]
Output:
1
Example 3
Input:
mat = [[0,0],[0,0]]
Output:
-1
Constraints
rows == mat.length
cols == mat[i].length
1 <= rows, cols <= 100
mat[i][j]
is either0
or1
.mat[i]
is sorted in non-decreasing order.
Approach and Intuition
Given the unique constraints and format of the problem, an efficient approach is crucial. Here's a step-by-step breakdown:
Get Dimensions: Use
BinaryMatrix.dimensions()
to retrieve the number of rows and columns.Start at Top-Right Corner:
- The intuition for starting at the top-right is it allows you to eliminate either a row or a column in each step, thus optimizing the search.
- If you find a
1
, you can move left (to reduce the column index) because there can't be a1
in any column to the right of the current one within the same row. - If you find a
0
, you should move down to the next row since there can't be a1
to the left in the same row, but there might be below in the same column.
Iterate until Boundaries are Reached:
- Continue the process until you either run out of columns or rows. If you exit the loop with a column index in the valid range, that's the leftmost column with a
1
. If not, return-1
.
- Continue the process until you either run out of columns or rows. If you exit the loop with a column index in the valid range, that's the leftmost column with a
This strategy ensures that each step provides maximal information, either confirming the absence of 1's
to the left or above, allowing us to make the least number of calls to BinaryMatrix.get
while unraveling the matrix effectively.
Examples Explained
For Example 1:
- Starting at the top-right
(0, 1)
gives0
, so move down. - At
(1, 1)
, it's1
, indicating the potential leftmost column, so move left. - At
(1, 0)
, it's1
again - confirming column 0 is indeed the leftmost with a1
.
For Example 2:
- Start at
(0, 1)
, move down because it's0
. - At
(1, 1)
, find1
- confirming column 1 is the leftmost with a1
as moving left leads to(1, 0)
, which is0
.
For Example 3:
- Checks confirm only
0
s present, returning-1
.
This approach leverages the matrix's sorted property and bounded interface calls to efficiently locate the desired column index.
Solutions
- Java
- Python
class Solution {
public int firstColumnWithOne(BinaryMatrix matrix) {
int numRows = matrix.dimensions().get(0);
int numCols = matrix.dimensions().get(1);
// Start from the top-right corner of the matrix
int row = 0;
int col = numCols - 1;
// Move towards the bottom-left corner
while (row < numRows && col >= 0) {
if (matrix.get(row, col) == 0) {
row++;
} else {
col--;
}
}
// Check if the column is the last one and full of zeros
return (col == numCols - 1) ? -1 : col + 1;
}
}
Given a binary matrix, the task is to find the leftmost column with at least a one using Java. The firstColumnWithOne
function presented determines this by:
- obtaining the number of rows and columns from the matrix using
matrix.dimensions().get(0)
andmatrix.dimensions().get(1)
. - starting from the top-right corner of the matrix and repeatedly moving either left or down based on the element value at the current position:
- If the element is "0", move downward to the next row.
- If the element is "1", move leftward to the previous column.
By iterating in such a manner, the search is efficient, reducing the area to be searched after each movement. The process stops when no further leftward or downward movements can be made because the boundaries of the matrix have been reached.
Finally, the function evaluates the position of the last column checked:
- If it ends at the last column without finding a 1, it returns
-1
. - Otherwise, it returns the index of the column found, adjusted by one to compensate for zero-based indexing.
This approach ensures that the algorithm efficiently pinpoints the leftmost column containing at least a single '1', making the solution optimal for potentially large matrices.
class Solution:
def findLeftmostOne(self, grid: 'BinaryMatrix') -> int:
# Retrieve the dimensions of the grid
num_rows, num_cols = grid.dimensions()
# Initialize the position as top-right corner
row_index = 0
col_index = num_cols - 1
# Traverse the grid until bounds are exceeded
while row_index < num_rows and col_index >= 0:
if grid.get(row_index, col_index) == 0:
row_index += 1
else:
col_index -= 1
# Check the position where we stopped to determine if a 1 was found
return col_index + 1 if col_index != num_cols - 1 else -1
The problem titled "Leftmost Column with at Least a One" requires determining the leftmost column index in a grid (like a matrix) where at least one '1' exists. The Python function findLeftmostOne
accepts a grid through the parameter grid
, which is an instance of the BinaryMatrix
class with methods to retrieve grid dimensions and values at specific coordinates.
Here's how the function works:
- First, retrieve the number of rows and columns in the grid.
- Start by positioning at the top-right corner of the grid.
- Employ a while loop to traverse the grid diagonally downwards to the left. In each iteration:
- If the value at the current position is '0', move one row down.
- If the value is '1', move one column to the left.
- Continue the process until the current position moves outside the bounds of the grid dimensions.
- After exiting the loop, if a '1' was found in any column, return its column index. If no '1' was found in any of the checked columns, return
-1
.
Follow these steps to effectively determine the leftmost column containing a '1'. This efficient approach ensures minimal traversal, reducing unnecessary checks and operates in a time complexity nearly linear to the dimensions of the grid.
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