cell2mat

Convert cell array to ordinary array

Syntax

A = cell2mat(C)

Description

A = cell2mat(C) converts a cell array to an ordinary array.

The contents of C must support concatenation into an N-dimensional rectangle. Otherwise, the results are undefined. For example, the contents of cells in the same column must have the same number of columns, although they need not have the same number of rows.

Examples

Convert Cell Array to Numeric Array

Convert numeric arrays in four cells of a cell array into one numeric array.

C = {[1],    [2 3 4];
     [5; 9], [6 7 8; 10 11 12]}

C=2×2 cell array
    {[       1]}    {[   2 3 4]}
    {2×1 double}    {2×3 double}

A = cell2mat(C)

A = 3×4

     1     2     3     4
     5     6     7     8
     9    10    11    12

Convert Cell Array of Structures to Array

Convert structures in a cell array into one structure array. The structures must have the same fields.

s1.a = [1 2 3 4];
s1.b = 'Good';
s2.a = [5 6; 7 8];
s2.b = 'Morning';
c = {s1,s2};
d = cell2mat(c)

d=1×2 struct array with fields:
    a
    b

Display the first field of structure d(1).

d(1).a

ans = 1×4

     1     2     3     4

Display the second field of d(2).

d(2).b

ans = 
'Morning'

Convert Cell Array Containing Different Data Types

Since R2025a

Convert a cell array containing different data types to an ordinary array.

Create a cell array that contains single and double values.

a = single([1 2 3]);
b = double([2 4 6]);
C = {a;b}

C =

  2×1 cell array

    {[1 2 3]}
    {[2 4 6]}

Convert the cell array to a numeric array. The resulting array is single.

D = cell2mat(C)

D =

  2×3 single matrix

     1     2     3
     2     4     6

Input Arguments

C — Input cell array

cell array

Input cell array. If the contents of the cells all have the same data type, the resulting array has that data type. The function can concatenate cells that contain structures if those structures have the same field names.

The cells can have different data types if MATLAB^® can convert the data types to one output type. For examples of basic data type combinations and their resulting types, see Valid Combinations of Unlike Classes.

cell2mat also accepts cell arrays containing class-based objects. For information on how class-based objects can be combined, see Concatenating Objects of Different Classes.

cell2mat does not accept nested cells within C.

Extended Capabilities

Tall Arrays

Calculate with arrays that have more rows than fit in memory.

The cell2mat function supports tall arrays with the following usage notes and limitations:

• The cells of the input cell array must contain numeric, logical, or character data types.

For more information, see Tall Arrays.

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• Code generation is not supported for cell2mat for unbounded or variable-size cell arrays containing sparse arrays.

• Arrays or structures present in unbounded or variable-size cell array input with a dimension greater than 2 are not supported for code generation with the cell2mat function.

• For a run-time empty-cell input, cell2mat returns an empty cell of the same data type. For a compile-time empty-cell input, cell2mat returns an empty cell of type double.

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™. (since R2025a)

The cell2mat function fully supports cell arrays containing gpuArray (Parallel Computing Toolbox) objects. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays

Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a

R2025a: Cell array elements can contain different data types

Before R2025a, cell2mat accepted numeric, logical, and character types, as well as structures with the same field names. All cells of the input array had to have the same data type.

cell2mat can now accept cell arrays containing additional data types, including strings, categoricals, gpuArray objects, and class-based objects.

The function can also convert a cell array that contains different data types if MATLAB can convert those data types to one output type. For examples of basic data type combinations and their resulting types, see Valid Combinations of Unlike Classes.

If the cell array contains class-based objects of different classes, MATLAB attempts to concatenate them. For more information, see Concatenating Objects of Different Classes.