Leetcode 498: Diagonal Traverse
You are given an m x n matrix. The task is to return an array that contains all the elements of the matrix in diagonal order, starting from the top-left and moving diagonally towards the bottom-right. The diagonal order alternates between upward and downward diagonals.
Problem
Approach
Steps
Complexity
Input: The input consists of an m x n matrix where each element is an integer.
Example: [[1,2,3],[4,5,6],[7,8,9]]
Constraints:
• 1 <= m, n <= 10^4
• 1 <= m * n <= 10^4
• -10^5 <= mat[i][j] <= 10^5
Output: The output is an array of integers, which represents all the elements of the matrix in diagonal order.
Example: [1, 2, 4, 7, 5, 3, 6, 8, 9]
Constraints:
• The output array contains all the elements from the matrix in diagonal order.
Goal: The goal is to traverse the matrix in diagonal order, alternating between upward and downward diagonals.
Steps:
• 1. Iterate over all diagonals, starting from the top-left corner.
• 2. For each diagonal, alternate the direction of traversal (upward or downward).
• 3. Add elements to the result array in the correct diagonal order.
Goal: The problem has the following constraints:
Steps:
• 1 <= m, n <= 10^4
• 1 <= m * n <= 10^4
• -10^5 <= mat[i][j] <= 10^5
Assumptions:
• The matrix will always have valid integer values.
• The matrix will have at least one element.
• Input: [[1,2,3],[4,5,6],[7,8,9]]
• Explanation: In this example, the elements are traversed diagonally starting from the top-left and moving towards the bottom-right, alternating between upward and downward diagonals.
Approach: The solution involves iterating over all diagonals and alternating the direction of traversal. Each element is added to the result array in the correct order.
Observations:
• The traversal alternates between upward and downward diagonals.
• We need to handle each diagonal separately and ensure the correct order of traversal.
• We can efficiently handle the diagonals by iterating over each one and managing the direction of traversal.
Steps:
• 1. Create a loop to iterate through diagonals, from the first element to the last.
• 2. For each diagonal, alternate the direction of traversal based on the diagonal's index.
• 3. Collect the elements from each diagonal in the result array.
Empty Inputs:
• The matrix will always contain at least one element.
Large Inputs:
• The solution must be efficient enough to handle large matrices (up to 10^4 elements).
Special Values:
• The matrix may contain negative and large values, but they should not affect the solution.
Constraints:
• Ensure the algorithm is optimized for large matrices, especially when m * n approaches 10^4.
vector<int> findDiagonalOrder(vector<vector<int>>& mat) {
int m = mat.size(), n = mat[0].size();
vector<int> res;
for(int s = 0; s <= m + n - 2; s++) {
for(int x = 0; x <= s; x++) {
int i = x;
int j = s - i;
if(s%2 == 0) swap(i, j);
if(i >= m || j >= n) continue;
res.push_back(mat[i][j]);
}
}
return res;
}
1 : Method Definition
vector<int> findDiagonalOrder(vector<vector<int>>& mat) {
Defines the method `findDiagonalOrder` which takes a 2D matrix `mat` and returns a vector of integers representing the diagonal order traversal.
2 : Variable Initialization
int m = mat.size(), n = mat[0].size();
Initializes variables `m` and `n` to store the number of rows and columns in the matrix `mat`, respectively.
3 : Variable Initialization
vector<int> res;
Declares a vector `res` that will store the result of the diagonal order traversal.
4 : Loop Structure
for(int s = 0; s <= m + n - 2; s++) {
Outer loop iterating over the sum `s` of the row and column indices. This loop will control the traversal of diagonals in the matrix.
5 : Loop Structure
for(int x = 0; x <= s; x++) {
Inner loop iterating over values `x` which represent the row index in the diagonal. It ensures all elements in the current diagonal are processed.
6 : Variable Assignment
int i = x;
Assigns the value of `x` to `i`, representing the row index of the current element in the diagonal.
7 : Variable Assignment
int j = s - i;
Calculates the column index `j` as `s - i`, ensuring that the sum of `i` and `j` is equal to `s`.
8 : Conditional Check
if(s%2 == 0) swap(i, j);
Checks if the sum `s` is even. If so, it swaps `i` and `j` to alternate the diagonal traversal direction.
9 : Boundary Check
if(i >= m || j >= n) continue;
Checks if the row index `i` or column index `j` is out of bounds of the matrix. If either is out of bounds, it skips the current iteration.
10 : Result Update
res.push_back(mat[i][j]);
Adds the matrix element at position `[i][j]` to the result vector `res`.
11 : Return Statement
return res;
Returns the result vector `res` containing the elements in diagonal order.
Best Case: O(m * n)
Average Case: O(m * n)
Worst Case: O(m * n)
Description: The time complexity is O(m * n) as we visit each element of the matrix once.
Best Case: O(m * n)
Worst Case: O(m * n)
Description: The space complexity is O(m * n) for storing the result array.
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