Given a matrix mat[][] of dimensions NxM, the task is to check whether the given matrix is balanced or not. Print “Balanced” if it is a balanced matrix else print “Unbalanced”.
A matrix is balanced if all cells in the matrix are balanced and a cell of the matrix is balanced if the number of cells in that matrix that are adjacent to that cell is strictly greater than the value written in this cell.
Adjacent cell means cells in the top, down, left, and right cell of each cell if it exists.
Examples:
Input: N = 3, M = 3
mat[][] = {{1, 2, 3},
{4, 5, 6},
{7, 8, 9}}
Output: Unbalanced
Explanation: Each cell of the given grid is not stable, so the overall grid is unbalanced.
Input: N = 3, M = 3
mat[][] = {{1, 2, 1},
{2, 3, 2},
{1, 2, 1}}
Output: Balanced
Explanation: Each cell of the given grid is stable, so the overall grid is Balanced.
Approach:
- Travers the given matrix mat[][].
- For each cell of the matrix check if all the adjacent cells i.e., mat[i+1][j], mat[i][j+1], mat[i-1][j], mat[i][j-1] are strictly smaller than the current cell.
- For the corner cells of the matrix, there are only two adjacent cells i.e., mat[i+1][j] and mat[i][j+1] check if all these adjacent cells are strictly smaller than the corner cell.
- For border cell of the matrix, there are 3 adjacent cells i.e., mat[i-1][j], mat[i+1][j], and mat[i][j+1] check if all these adjacent cells are strictly smaller than the border cell.
- If all the above conditions are true for all the cells of the matrix then print “Balanced” else print “Unbalanced”.
Below is the implementation of the above approach:
C++
// C++ program for the above approach #include <bits/stdc++.h> using namespace std; // Define size of matrix #define N 4 #define M 4 // Function to check given matrix // balanced or unbalanced string balancedMatrix( int mat[][M]) { // Flag for check matrix is balanced // or unbalanced bool is_balanced = true ; // Iterate row until condition is true for ( int i = 0; i < N && is_balanced; i++) { // Iterate cols until condition is true for ( int j = 0; j < M && is_balanced; j++) { // Check for corner edge elements if ((i == 0 || i == N - 1) && (j == 0 || j == M - 1)) { if (mat[i][j] >= 2) is_balanced = false ; } // Check for border elements else if (i == 0 || i == N - 1 || j == 0 || j == M - 1) { if (mat[i][j] >= 3) is_balanced = false ; } else { // Check for the middle ones if (mat[i][j] >= 4) is_balanced = false ; } } } // Return balanced or not if (is_balanced) return "Balanced" ; else return "Unbalanced" ; } // Driver Code int main() { // Given Matrix mat[][] int mat[N][M] = { { 1, 2, 3, 4 }, { 3, 5, 2, 6 }, { 5, 3, 6, 1 }, { 9, 5, 6, 0 } }; // Function Call cout << balancedMatrix(mat); return 0; } |
Java
// Java program for the above approach import java.util.*; class GFG{ // Define size of matrix static final int N = 4 ; static final int M = 4 ; // Function to check given matrix // balanced or unbalanced static String balancedMatrix( int mat[][]) { // Flag for check matrix is balanced // or unbalanced boolean is_balanced = true ; // Iterate row until condition is true for ( int i = 0 ; i < N && is_balanced; i++) { // Iterate cols until condition is true for ( int j = 0 ; j < M && is_balanced; j++) { // Check for corner edge elements if ((i == 0 || i == N - 1 ) && (j == 0 || j == M - 1 )) { if (mat[i][j] >= 2 ) is_balanced = false ; } // Check for border elements else if (i == 0 || i == N - 1 || j == 0 || j == M - 1 ) { if (mat[i][j] >= 3 ) is_balanced = false ; } else { // Check for the middle ones if (mat[i][j] >= 4 ) is_balanced = false ; } } } // Return balanced or not if (is_balanced) return "Balanced" ; else return "Unbalanced" ; } // Driver Code public static void main(String[] args) { // Given Matrix mat[][] int mat[][] = {{ 1 , 2 , 3 , 4 }, { 3 , 5 , 2 , 6 }, { 5 , 3 , 6 , 1 }, { 9 , 5 , 6 , 0 }}; // Function Call System.out.print(balancedMatrix(mat)); } } // This code is contributed by shikhasingrajput |
Python3
# Python3 program for the above approach # Define the size of the matrix N = 4 M = 4 # Function to check given matrix # balanced or unbalanced def balancedMatrix(mat): # Flag for check matrix is balanced # or unbalanced is_balanced = True # Iterate row until condition is true i = 0 while i < N and is_balanced: # Iterate cols until condition is true j = 0 while j < N and is_balanced: # Check for corner edge elements if ((i = = 0 or i = = N - 1 ) and (j = = 0 or j = = M - 1 )): if mat[i][j] > = 2 : isbalanced = False # Check for border elements elif (i = = 0 or i = = N - 1 or j = = 0 or j = = M - 1 ): if mat[i][j] > = 3 : is_balanced = False # Check for the middle ones else : if mat[i][j] > = 4 : is_balanced = False j + = 1 i + = 1 # Return balanced or not if is_balanced: return "Balanced" else : return "Unbalanced" # Driver code # Given matrix mat[][] mat = [ [ 1 , 2 , 3 , 4 ], [ 3 , 5 , 2 , 6 ], [ 5 , 3 , 6 , 1 ], [ 9 , 5 , 6 , 0 ] ] # Function call print (balancedMatrix(mat)) # This code is contributed by Stuti Pathak |
C#
// C# program for the above approach using System; class GFG{ // Define size of matrix static readonly int N = 4; static readonly int M = 4; // Function to check given matrix // balanced or unbalanced static String balancedMatrix( int [, ]mat) { // Flag for check matrix is balanced // or unbalanced bool is_balanced = true ; // Iterate row until condition is true for ( int i = 0; i < N && is_balanced; i++) { // Iterate cols until condition is true for ( int j = 0; j < M && is_balanced; j++) { // Check for corner edge elements if ((i == 0 || i == N - 1) && (j == 0 || j == M - 1)) { if (mat[i, j] >= 2) is_balanced = false ; } // Check for border elements else if (i == 0 || i == N - 1 || j == 0 || j == M - 1) { if (mat[i, j] >= 3) is_balanced = false ; } else { // Check for the middle ones if (mat[i, j] >= 4) is_balanced = false ; } } } // Return balanced or not if (is_balanced) return "Balanced" ; else return "Unbalanced" ; } // Driver Code public static void Main(String[] args) { // Given Matrix [,]mat int [, ]mat = {{1, 2, 3, 4}, {3, 5, 2, 6}, {5, 3, 6, 1}, {9, 5, 6, 0}}; // Function Call Console.Write(balancedMatrix(mat)); } } // This code is contributed by 29AjayKumar |
Unbalanced
Time Complexity: O(N*M)
Auxiliary Space: O(1)
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