/*This Java Program is to Implement Sparse Matrix.In the subfield of numerical analysis, a sparse matrix is a matrix populated primarily with zeros (Stoer & Bulirsch 2002, p. 619) as elements of the table. By contrast, if a larger number of elements differ from zero, then it is common to refer to the matrix as a dense matrix. The fraction of zero elements (non-zero elements) in a matrix is called the sparsity (density).*/ public class SparseMatrix { private int N; private SparseArray sparsearray[]; public SparseMatrix(int N) { this.N = N; sparsearray = new SparseArray[N]; for (int index = 0; index < N; index++) { sparsearray[index] = new SparseArray(N); } } public void store(int rowindex, int colindex, Object value) { if (rowindex < 0 || rowindex > N) throw new RuntimeException("row index out of bounds"); if (colindex < 0 || colindex > N) throw new RuntimeException("col index out of bounds"); sparsearray[rowindex].store(colindex, value); } public Object get(int rowindex, int colindex) { if (rowindex < 0 || colindex > N) throw new RuntimeException("row index out of bounds"); if (rowindex < 0 || colindex > N) throw new RuntimeException("col index out of bounds"); return (sparsearray[rowindex].fetch(colindex)); } public static void main(String... arg) { Integer[][] iarray = new Integer[3][3]; iarray[0][0] = 1; iarray[0][1] = null; iarray[0][2] = 2; iarray[1][0] = null; iarray[1][1] = 3; iarray[1][2] = null; iarray[2][0] = 4; iarray[2][1] = 6; iarray[2][2] = null; SparseMatrix sparseMatrix = new SparseMatrix(3); for (int rowindex = 0; rowindex < 3; rowindex++) { for (int colindex = 0; colindex < 3; colindex++) { sparseMatrix.store(rowindex, colindex, iarray[rowindex][colindex]); } } System.out.println("the sparse Matrix is "); for (int rowindex = 0; rowindex < 3; rowindex++) { for (int colindex = 0; colindex < 3; colindex++) { System.out.print(sparseMatrix.get(rowindex, colindex) + "\t"); } System.out.println(); } } } class List { private int index; private Object value; private List nextindex; public List(int index) { this.index = index; nextindex = null; value = null; } public List() { index = -1; value = null; nextindex = null; } public void store(int index, Object value) { List current = this; List previous = null; List node = new List(index); node.value = value; while (current != null && current.index < index) { previous = current; current = current.nextindex; } if (current == null) { previous.nextindex = node; } else { if (current.index == index) { System.out.println("DUPLICATE INDEX"); return; } previous.nextindex = node; node.nextindex = current; } return; } public Object fetch(int index) { List current = this; Object value = null; while (current != null && current.index != index) { current = current.nextindex; } if (current != null) { value = current.value; } else { value = null; } return value; } public int elementCount() { int elementCount = 0; for (List current = this.nextindex; (current != null); current = current.nextindex) { elementCount++; } return elementCount; } } public class SparseArray { private List start; private int index; SparseArray(int index) { start = new List(); this.index = index; } public void store(int index, Object value) { if (index >= 0 && index < this.index) { if (value != null) start.store(index, value); } else { System.out.println("INDEX OUT OF BOUNDS"); } } public Object fetch(int index) { if (index >= 0 && index < this.index) return start.fetch(index); else { System.out.println("INDEX OUT OF BOUNDS"); return null; } } public int elementCount() { return start.elementCount(); } } /* the sparse Matrix is 1 null 2 null 3 null 4 6 null