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Java

/*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