package com.thealgorithms.misc;
import java.util.Scanner;
/*
*A matrix is sparse if many of its coefficients are zero (In general if 2/3rd of matrix elements
*are 0, it is considered as sparse). The interest in sparsity arises because its exploitation can
*lead to enormous computational savings and because many large matrix problems that occur in
*practice are sparse.
*
* @author Ojasva Jain
*/
final class Sparsity {
private Sparsity() {
}
/*
* @return Sparsity of matrix
*
* where sparsity = number of zeroes/total elements in matrix
*
*/
static double sparsity(double[][] mat) {
int zero = 0;
// Traversing the matrix to count number of zeroes
for (int i = 0; i < mat.length; i++) {
for (int j = 0; j < mat[i].length; j++) {
if (mat[i][j] == 0) {
zero++;
}
}
}
// return sparsity
return ((double) zero / (mat.length * mat[1].length));
}
// Driver method
public static void main(String[] args) {
Scanner in = new Scanner(System.in);
System.out.println("Enter number of rows in matrix: ");
int n = in.nextInt();
System.out.println("Enter number of Columns in matrix: ");
int m = in.nextInt();
System.out.println("Enter Matrix elements: ");
double[][] mat = new double[n][m];
for (int i = 0; i < n; i++) {
for (int j = 0; j < m; j++) {
mat[i][j] = in.nextDouble();
}
}
System.out.println("Sparsity of matrix is: " + sparsity(mat));
in.close();
}
}