Hello, budding programmer! Are you ready to embark on a journey into the land of matrices? In this unit, we're in for a thrilling ride into the world of unique matrix traversal. We'll be navigating through the realm of 2D arrays following an intriguing and distinctive order. Stay seated, and let's dive right in!

Suppose we have a matrix where each cell represents a distinct symbol or integer. Our task is to decode this matrix by reading the cells in a particular order.

The decoding begins from the top-left cell of the matrix. We move in a bottom-left downward diagonal direction until we hit the left boundary. Upon hitting the left boundary, we move one cell down (unless we're at the bottom-left corner already, in which case we move one cell to the right) and start moving in an upward diagonal direction toward the upper-right.

While moving diagonally up-right, if we hit the top boundary, we move one cell to the right and start moving in a downward diagonal direction toward the bottom-left. However, if we hit the right boundary while moving diagonally upward, we move one cell down and start moving in a bottom-left direction. In other words, we keep zigzagging diagonally across the matrix until every cell in the matrix is visited.

Upon completing this zigzag traversal, we will have a list of traversed cell values. Next, we process this list to uncover the indices of the perfect square numbers. The function should implement this traversal and return a list containing the 1-indexed positions of perfect square numbers in the traversed sequence.

Take a 3x4 matrix, for instance:

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1{
2    {1, 2, 3, 4},
3    {5, 6, 7, 8},
4    {9, 10, 11, 12}
5}

Upon completing the diagonal traversal, we'll get the list: {1, 5, 2, 3, 6, 9, 10, 7, 4, 8, 11, 12}. From this list, we see that 1, 9, and 4 are perfect squares and are located at the 1st, 6th, and 9th positions (1-indexed) in the list. Thus, our function returns: {1, 6, 9}.

To tackle this problem, we will take the following steps:

• Traverse the Matrix Diagonally: Begin from the top-left cell and zigzag through the matrix in a specific diagonal pattern.
• Record Traversed Values: As you traverse, collect the cell values in a list.
• Identify Perfect Squares: Inspect the collected values to determine which are perfect squares.
• Return Positions: Gather the 1-indexed positions of the perfect squares in the list and return them.

First, let's scrutinize the dimensions of the matrix. To map the landscape of our matrix, we'll use len(matrix) to determine the number of rows and len(matrix[0]) to determine the number of columns. Next, we initialize two slices: traversal and results. The traversal slice will be responsible for keeping the cell values that we will obtain from the matrix based on our unique diagonal zigzag traversal. The results slice will be populated later with the 1-indexed positions of perfect square numbers that can be found in the traversal slice.

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1package main
2
3import (
4    "fmt"
5    "math"
6)
7
8func DiagonalTraverseAndSquares(matrix [][]int) []int {
9    rows := len(matrix)
10    cols := len(matrix[0])
11    traversal := []int{}
12    results := []int{}

To traverse the matrix diagonally in a zigzag pattern, we need to adhere to a specific movement strategy that alternates between two directions: down-left and up-right. Here's a clearer breakdown of the traversal logic.

1. Initialize Variables: We start by initializing row and col to zero, representing the top-left position of the matrix. We also set dir to 1 for the initial down-left direction.

2. Traverse the Matrix: We loop through each cell in the matrix using a loop that runs rows * cols times, which is the total number of elements in the matrix.

3. Add Current Value: In each iteration, add the current matrix element located at (row, col) to the traversal slice.

4. Determine Move Direction:

   • Direction = 1 (down-left):
     • If row == rows - 1 (bottom boundary), move one step right (col += 1) and change direction to up-right (dir = -1).
     • If col == 0 (left boundary), move one step down (row += 1) and change direction to up-right (dir = -1).
     • Otherwise, move diagonally down-left (row += 1; col -= 1).
   • Direction = -1 (up-right):
     • If col == cols - 1 (right boundary), move one step down (row += 1) and change direction to down-left (dir = 1).
     • If row == 0 (top boundary), move one step right (col += 1) and change direction to down-left (dir = 1).
     • Otherwise, move diagonally up-right (row -= 1; col += 1).

This approach ensures that the traversal covers all cells in a zigzag manner while respecting the matrix boundaries.

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1    row, col, dir := 0, 0, 1
2    for i := 0; i < rows*cols; i++ {
3        traversal = append(traversal, matrix[row][col])  // Append current cell value to traversal slice
4
5        // Determine next position based on current direction
6        if dir == 1 {  // Moving down-left
7            if row == rows-1 {  // Hit bottom boundary
8                col += 1
9                dir = -1  // Switch direction to up-right
10            } else if col == 0 {  // Hit left boundary
11                row += 1
12                dir = -1  // Switch direction to up-right
13            } else {
14                row += 1
15                col -= 1  // Continue down-left
16            }
17        } else {  // Moving up-right
18            if col == cols-1 {  // Hit right boundary
19                row += 1
20                dir = 1  // Switch direction to down-left
21            } else if row == 0 {  // Hit top boundary
22                col += 1
23                dir = 1  // Switch direction to down-left
24            } else {
25                row -= 1
26                col += 1  // Continue up-right
27            }
28        }
29    }

This detailed explanation should help in understanding how each movement decision contributes to the zigzag traversal pattern across the matrix.

With a completed traversal, we have obtained a slice of integers. Next, we evaluate this slice to identify perfect squares — numbers that are the squares of integers. In Go, we can utilize math.Sqrt to test whether a given number is a perfect square. If the square root of the number, when floored, remains unchanged, the number is a perfect square. For each perfect square in the traversal slice, we add its 1-indexed position to the results slice.

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1    for idx, val := range traversal {
2        root := math.Sqrt(float64(val))
3        if root == float64(int(root)) {  // Check if the value is a perfect square number.
4            results = append(results, idx+1)
5        }
6    }
7
8    return results
9}

Let's see how to use the DiagonalTraverseAndSquares function we have developed. Suppose we have a 4x4 matrix:

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1func main() {
2    matrix := [][]int{
3        {16, 2, 3, 13},
4        {5, 11, 10, 8},
5        {9, 7, 6, 12},
6        {4, 14, 15, 1},
7    }
8
9    result := DiagonalTraverseAndSquares(matrix)
10    fmt.Println(result)  // Output: [1, 6, 7, 16]
11}

Here's what's going on:

1. We define a 4x4 matrix matrix.
2. We call the DiagonalTraverseAndSquares function with matrix as its argument.
3. The function returns a slice [1, 6, 7, 16], which represents the 1-indexed positions of perfect square numbers in the traversed sequence.

For further verification, let's decode this traversal step by step:

1. Diagonal traversal sequence: {16, 5, 2, 3, 11, 9, 4, 7, 10, 13, 8, 6, 14, 15, 12, 1}
2. Perfect squares in the sequence: 16 (1st), 9 (6th), 4 (7th), 1 (16th)

Thus, the 1-indexed positions of perfect squares are correctly identified as [1, 6, 7, 16].

Bravo! You've successfully navigated a challenging task involving a unique matrix traversal pattern. You've demonstrated solid skills in Go programming, especially in slice manipulation, and tackled the challenges of moving around two-dimensional arrays with finesse. Now, it's time to put your newly learned skills to the test! Try out more complex matrices and different values to truly master the concept. Keep experimenting, and you'll soon become a wizard at matrix traversals. Happy coding!