Saturday, April 4, 2015

Java program to multiply two matrices

Java program to multiply two matrices

This java program multiply two matrices. Before multiplication matrices are checked whether they can be multiplied or not.

Java programming code

import java.util.Scanner;
 
class MatrixMultiplication
{
   public static void main(String args[])
   {
      int m, n, p, q, sum = 0, c, d, k;
 
      Scanner in = new Scanner(System.in);
      System.out.println("Enter the number of rows and columns of first matrix");
      m = in.nextInt();
      n = in.nextInt();
 
      int first[][] = new int[m][n];
 
      System.out.println("Enter the elements of first matrix");
 
      for ( c = 0 ; c < m ; c++ )
         for ( d = 0 ; d < n ; d++ )
            first[c][d] = in.nextInt();
 
      System.out.println("Enter the number of rows and columns of second matrix");
      p = in.nextInt();
      q = in.nextInt();
 
      if ( n != p )
         System.out.println("Matrices with entered orders can't be multiplied with each other.");
      else
      {
         int second[][] = new int[p][q];
         int multiply[][] = new int[m][q];
 
         System.out.println("Enter the elements of second matrix");
 
         for ( c = 0 ; c < p ; c++ )
            for ( d = 0 ; d < q ; d++ )
               second[c][d] = in.nextInt();
 
         for ( c = 0 ; c < m ; c++ )
         {
            for ( d = 0 ; d < q ; d++ )
            {   
               for ( k = 0 ; k < p ; k++ )
               {
                  sum = sum + first[c][k]*second[k][d];
               }
 
               multiply[c][d] = sum;
               sum = 0;
            }
         }
 
         System.out.println("Product of entered matrices:-");
 
         for ( c = 0 ; c < m ; c++ )
         {
            for ( d = 0 ; d < q ; d++ )
               System.out.print(multiply[c][d]+"\t");
 
            System.out.print("\n");
         }
      }
   }
}
Download Matrix multiplication program class file.
Output of program:
matrix multiply
This is a basic method of multiplication, there are more efficient algorithms available. Also this approach is not recommended for sparse matrices which contains a large number of elements as zero.

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