package com.thealgorithms.misc;
/*
*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() {
}
/*
* @param mat the input matrix
* @return Sparsity of matrix
*
* where sparsity = number of zeroes/total elements in matrix
*
*/
static double sparsity(double[][] mat) {
if (mat == null || mat.length == 0) {
throw new IllegalArgumentException("Matrix cannot be null or empty");
}
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[0].length));
}
}