Given a square matrix, calculate the absolute difference between the sums of its diagonals

Sure, here is a step-by-step guide on how to calculate the absolute difference between the sums of the diagonals of a square matrix:

1. First, you need to identify the elements of the two diagonals. In a square matrix, the elements of the primary diagonal are those where the row index and column index are the same (i.e., matrix[i][i] for i ranging from 0 to the size of the matrix - 1). The elements of the secondary diagonal are those where the row index and the column index sum up to the size of the matrix minus 1 (i.e., matrix[i][size-i-1] for i ranging from 0 to the size of the matrix - 1).

2. Once you have identified the elements of the two diagonals, sum up the elements of each diagonal separately.

3. Finally, subtract the sum of the elements of one diagonal from the sum of the elements of the other diagonal and take the absolute value of the result. This will give you the absolute difference between the sums of the diagonals of the square matrix.

Here is a Python code snippet that implements these steps:

def diagonal_difference(matrix):
    size = len(matrix)
    diag1_sum = sum(matrix[i][i] for i in range(size))
    diag2_sum = sum(matrix[i][size-i-1] for i in range(size))
    return abs(diag1_sum - diag2_sum)

In this function, matrix is a 2D list representing the square matrix. The function returns the absolute difference between the sums of the diagonals.