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Let us assume a sparse matrix from storage view point. Assume that the entire sparse matrix is stored. Then, a significant amount of memory that stores the matrix consists of zeroes. It is nothing but wastage of memory. In real life, such wastage might count to megabytes. Thus, an efficient method of storing sparse matrices ought to be looked into.
Figure illustrates a sparse matrix of order 7 × 6.
0
1
2
3
4
5
9
6
8
Figure: Representation of a sparse matrix of order 7 × 6
A general way of representing non zero elements of any sparse matrix is the 3-tuple form. The primary row of sparse matrix always indicates the number of columns, the number of rows, & number of non zero elements in the matrix. The number seven represents the entire number of rows sparse matrix. Alike, in the matrix the number six represents the total number of columns. The number eight represents the overall number of non zero elements in the matrix. Each of non zero element is stored from the second row, along the 1st & 2nd elements of the row, mentioning the row number & column number respectively wherein the element is present in the original matrix. In this row the 3rd element stores the actual value of the non zero element. For instance, the 3- tuple representation of the matrix of Figure is illustrated in Figure
Figure: tuple representation of above figure
The following program 1 accepts a matrix as input that is sparse & prints the corresponding 3-tuple representations.
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