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In this article, you will get to know about:

  1. 2-D array and how to represent it in memory
  2. Multi-dimensional array

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  1. Two-dimensional arrays

                                 2-d array

  • A 2-D array is a list of a finite number m×n of homogenous data elements.
  • The elements of the array are referred by two index sets consisting of m and n consecutive integer numbers. 
  • The elements of the array are stored in consecutive memory location.
  • 2-D arrays are called matrices in mathematics and tables in business applications

  1. Representing 2D array in memory



  • The elements are stored column by column i. e. m elements of first column and stored in first m locations, elements of the second column are stored in next m locations and so on.

                                                  row major order

  • The elements are sorted row by row for n elements.

For 2-D array a of size m×n , using the base address of a[i][j] element by:

In column major order

loc(a[i][j]) =base(a) +w(m*j+i)

 In row major order

loc (a[i][j])=base(a) +w(n*i+j)

where, w=width i. e. number of bytes taken by each element

 m=total number of rows

n=total number of columns

Note:The product A×B of two matrices A and B is defined only when the number of columns in A equals to the number of rows in B.

Square Matrix

  • A square matrix has the same number of rows and columns.
  • Some special form of square matrix are:
  • Diagonal matrix
  • Tridiagonal matrix
  • Lower triangular matrix
  • Upper triangular matrix

Diagonal matrix

  • A matrix B is diagonal iff B(i,j) =0 for i≠j
  • The  diagonal matrix can be stored as 1-D array to reduce memory space.

 Tridiagonal matrix

  • A matrix B is trdiagonal iff B(i,j) =0 for |i-j|>1
  • In a n×n tridiagonal matrix B, the non-zero elements lie on one of the three diagonals.
  • Main diagonal , for which i=j.It has n elements.
  • Diagonal below main diagonal, for which i=j+1.It has n-1 elements.
  • Diagonal above main diagonal, for which i=j-1.It has n-1 elements.
  • It has 3n-2 non-zero elements.
  • The elements of tridiagonal matrix can be mapped up by following ways
  • Row wise
  • Column wise
  • Diagonal wise beginning with the lowest.

Triangular matrix 

Lower triangular matrix 

  • A matrix B is lower triangular iff B(i,j) =0 for i<j

Upper triangular matrix

  • A matrix B is upper triangular iff B(i,j) =0 for i>j

  • Total number of non-zero elements in triangular matrix is n(n+1) /2

Sparse Matrix

  • A m×n matrix A is said to be sparse if many of its elements are zero. 
  • Matrix that is not sparse is known as dense matrix.
  • It is not possible to define an exact boundary between dense and sparse matrices.
  • The diagonal and tridiagonal matrices fit into the category of sparse matrices.

Array representation of sparse matrices

  • In array representation, an array of triplets of type
  • <row,col,element>
  • is used to store non-zero elements, where first field of the triplet is used to record row position, second to record column position and third one to record non-zero element of the sparse matrix. 
  • In addition, we need to record the size of the matrix(i.e. number of rows and columns) and non-zero elements. For this purpose, the first element of array triplet is used, where first field stores number of rows, second field stores number of non-zero elements . The remanining elements of the array store non-zero elements of the sparse matrix on row major order.

  1. Multi-Dimensional Array

multi dimensional array

  • A linear array can be called 1-D array, since each element in the array is referred by a single subscript.
  • A 2-D ‘m×n’ array is a collection of m. n data elements such that each element is specified called subscriptsA[i],[j]
  • A 3-D array ‘m×n×s’ . Then it contains m. n. elements.
  • For example, Suppose B is a three dimensional 2×4×3 array, then B contains 2.4.3=24 elements.

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