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# Mat2cell in Matlab

‘mat2cell’ function in Matlab converts arrays or vectors or multidimensional matrix into smaller cell arrays or vectors or multidimensional matrix. The basic principle behind this concept is to convert a matrix into the cells. It converts only dimensions and formats of the matrix without changing elements that means there is no data loss in this function. This function can be performed in two ways one way is by providing rows distribution and another way is by providing rows as well as columns distribution. By using this function we are changing dimensions of the matrix but we can again restore our original data or elements by using mat2cell function.

### Syntax:

Below is the syntax for Mat2cell Matlab:

``````Op = mat2cell (in, [ 4 3 ] )
Output variable name = mat2cell (input variable name, [ rows of first matrix rows of second matrix ]``````

OR

``````Op = mat2cell (in , [ 3 2 ] , [ 2 3 ] )
Output variable name = mat2cell ( input variable name , [ first sub - matrix dimensions second sub - matrix dimensions ]``````

## How does Mat2cell Matlab work?

Mat2cell function needs some parameters to operate on input .in the first way we need to provide row distribution of matrix to the function. Suppose there are 4 rows in input then row distribution  for output will be [ 1 3 ] or [ 2 2 ] or [ 3 1 ] or [40] or [04]. In the second approach, we need to provide cell array dimensions. Suppose there are 3 rows and 4 columns in the input matrix, so dimensions of the input matrix will be 3 by 4. Then distributions are such that [ 2 1 ] [ 2 2 ]. Distribution should be the addition of dimensions of submatrices. There are other distributions also processed for this example like [ 3 1 ][ 1 2 ] or [ 1 2 ] [ 3 1 ].

## Examples to Implement Mat2cell Matlab

Below are examples mentioned:

## Example 1:

Let us assume one input matrix with three rows and three columns, here the input matrix is assigned to variable ‘in’ and the output matrix is assigned to variable ‘op’. In this example, we have used the multi-dimensions approach. First matrix dimensions are [ 2 1 ] and second dimensions are [ 1 2 ].

## Code:

``````clc ;
clear all ;
in = [ 5 43 2 ; 4 5 33 ; 4 56 7 ] op = mat2cell( in ,[ 2 1 ],[ 1 2 ] )``````

## Example 2:

In this example, we assume a matrix of three rows and five columns that means the size of the input matrix is three by five here input matrix is assigned to variable ‘in’, and the output matrix is assigned to variable ‘op’. We have used a sub-matrix dimensions approach to convert the input matrix into cell-matrix. Dimensions of submatrix are [ 2 1 ] and [ 3 2 ], so that satisfies criteria of the addition of rows and columns, that is two plus three is five, and one plus two is three. We also observe the result by using a size function. Size of the input matrix is [ 3 5 ] and the size of the output matrix is [ 2 2 ]

## Code:

``````clc ;
clear all ;
in = [ 43 45 66 76 0 ; 3 4 32 22 19 ; 67 56 44 34 32 ] display ( 'size of input matrix ' )
size ( in )
op = mat2cell ( in , [ 2 1 ] , [ 3 2 ] )
display ( ' size of output matrix ' )
size( op )``````

## Example 3:

In this example we can see another approach of distribution that is only row distribution, here the input matrix is assigned to variable ‘in’, and the output matrix is assigned to variable ‘op’. Let us assume an input matrix of four rows and three columns that means size of the input matrix is three by four. We have applied mat2 cell function with row distribution [ 1 2 ]. Row distribution [ 1 2 ] means there will be two cell-matrix first matrix will have one row with four columns and the second matrix will have two rows with four columns. This approach changes only rows of dimensions and columns dimensions remain as it is.

## Code:

``````clc ;
clear all ;
in = [ 3.4 3.2 3.6 1.2 ; 1.1 1.4 5.3 2.1 ; 6.4 2.3 7.8 9.9 ] display ( ' size of input matrix ' )
size ( in )
op = mat2cell ( in , [ 1 2 ])
display ( 'size of output matrix' )
size ( op )``````