repmat

Repeat copies of array

Syntax

B = repmat(A,n)

B = repmat(A,r1,...,rN)

B = repmat(A,r)

Description

B = repmat(A,n) returns an array containing n copies of A in the row and column dimensions. The size of B is size(A)*n when A is a matrix.

B = repmat(A,r1,...,rN) specifies a list of scalars, r1,..,rN, that describes how copies of A are arranged in each dimension. When A has N dimensions, the size of B is size(A).*[r1...rN]. For example, repmat([1 2; 3 4],2,3) returns a 4-by-6 matrix.

B = repmat(A,r) specifies the repetition scheme with row vector r. For example, repmat(A,[2 3]) returns the same result as repmat(A,2,3).

Examples

Initialize Matrix with Same Element Value

Create a 3-by-2 matrix whose elements contain the value 10.

A = repmat(10,3,2)

A = 3×2

    10    10
    10    10
    10    10

Square Block Format

Repeat copies of a matrix into a 2-by-2 block arrangement.

A = diag([100 200 300])

A = 3×3

   100     0     0
     0   200     0
     0     0   300

B = repmat(A,2)

B = 6×6

   100     0     0   100     0     0
     0   200     0     0   200     0
     0     0   300     0     0   300
   100     0     0   100     0     0
     0   200     0     0   200     0
     0     0   300     0     0   300

Rectangular Block Format

Repeat copies of a matrix into a 2-by-3 block arrangement.

A = diag([100 200 300])

A = 3×3

   100     0     0
     0   200     0
     0     0   300

B = repmat(A,2,3)

B = 6×9

   100     0     0   100     0     0   100     0     0
     0   200     0     0   200     0     0   200     0
     0     0   300     0     0   300     0     0   300
   100     0     0   100     0     0   100     0     0
     0   200     0     0   200     0     0   200     0
     0     0   300     0     0   300     0     0   300

3-D Block Array

Repeat copies of a matrix into a 2-by-3-by-2 block arrangement.

A = [1 2; 3 4]

A = 2×2

     1     2
     3     4

B = repmat(A,[2 3 2])

B = 
B(:,:,1) =

     1     2     1     2     1     2
     3     4     3     4     3     4
     1     2     1     2     1     2
     3     4     3     4     3     4


B(:,:,2) =

     1     2     1     2     1     2
     3     4     3     4     3     4
     1     2     1     2     1     2
     3     4     3     4     3     4

Vertical Stack of Row Vectors

Vertically stack a row vector four times.

A = 1:4;
B = repmat(A,4,1)

B = 4×4

     1     2     3     4
     1     2     3     4
     1     2     3     4
     1     2     3     4

Horizontal Stack of Column Vectors

Horizontally stack a column vector four times.

A = (1:3)';  
B = repmat(A,1,4)

B = 3×4

     1     1     1     1
     2     2     2     2
     3     3     3     3

Tabular Block Format

Create a table with variables Age and Height.

A = table([39; 26],[70; 63],'VariableNames',{'Age' 'Height'})

A=2×2 table
    Age    Height
    ___    ______

    39       70  
    26       63  

Repeat copies of the table into a 2-by-3 block format.

B = repmat(A,2,3)

B=4×6 table
    Age    Height    Age_1    Height_1    Age_2    Height_2
    ___    ______    _____    ________    _____    ________

    39       70       39         70        39         70   
    26       63       26         63        26         63   
    39       70       39         70        39         70   
    26       63       26         63        26         63   

repmat repeats the entries of the table and appends a number to the new variable names.

Combine Vector Elements

Create two column vectors.

A = [1; 3; 5];
B = [2; 4];

Generate all element combinations of the two vectors by using repelem and repmat. Each row of the output T is a combination with the first element coming from the first vector and the second element coming from the second vector. This command is equivalent to finding the Cartesian product of two vectors.

T = [repelem(A,numel(B)) repmat(B,numel(A),1)]

T = 6×2

     1     2
     1     4
     3     2
     3     4
     5     2
     5     4

Starting in R2023a, you can also use the combinations function to generate all element combinations of two vectors.

T = combinations(A,B)

T=6×2 table
    A    B
    _    _

    1    2
    1    4
    3    2
    3    4
    5    2
    5    4

Input Arguments

A — Input array

scalar | vector | matrix | multidimensional array

Input array, specified as a scalar, vector, matrix, or multidimensional array.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical | char | string | struct | table | datetime | duration | calendarDuration | categorical | cell
Complex Number Support: Yes

n — Number of times to repeat input array in row and column dimensions

integer value

Number of times to repeat the input array in the row and column dimensions, specified as an integer value. If n is 0 or negative, the result is an empty array.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

r1,...,rN — Repetition factors for each dimension (as separate arguments)

integer values

Repetition factors for each dimension, specified as separate arguments of integer values. If any repetition factor is 0 or negative, the result is an empty array.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

r — Vector of repetition factors for each dimension (as a row vector)

integer values

Vector of repetition factors for each dimension, specified as a row vector of integer values. If any value in r is 0 or negative, the result is an empty array.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Tips

• To build block arrays by forming the tensor product of the input with an array of ones, use kron. For example, to stack the row vector A = 1:3 four times vertically, you can use B = kron(A,ones(4,1)).

• To create block arrays and perform a binary operation in a single pass, use bsxfun. In some cases, bsxfun provides a simpler and more memory efficient solution. For example, to add the vectors A = 1:5 and B = (1:10)' to produce a 10-by-5 array, use bsxfun(@plus,A,B) instead of repmat(A,10,1) + repmat(B,1,5).

• When A is a scalar of a certain type, you can use other functions to get the same result as repmat.

  repmat Syntax	Equivalent Alternative
  repmat(NaN,m,n)	NaN(m,n)
  repmat(single(inf),m,n)	inf(m,n,'single')
  repmat(int8(0),m,n)	zeros(m,n,'int8')
  repmat(uint32(1),m,n)	ones(m,n,'uint32')
  repmat(eps,m,n)	eps(ones(m,n))

Extended Capabilities

Tall Arrays

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

This function supports tall arrays with the limitations:

• The replication factor in the first dimension must be 1. For example, repmat(TA,1,n,p,...).

For more information, see Tall Arrays.

C/C++ Code Generation

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

Usage notes and limitations:

• Size arguments must have a fixed size.

• For sparse matrices, the repmat function does not support trailing ones as inputs after the first two dimensions.

GPU Code Generation

Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

• Size arguments must have a fixed size.

• For sparse matrices, the repmat function does not support trailing ones as inputs after the first two dimensions.

HDL Code Generation
Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL Coder™.

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™.

The repmat function fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray (Parallel Computing Toolbox). 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

R2019b: Some repetition arguments produce error

Starting in R2019b, some syntaxes involving nonscalar or empty repetition arguments will produce an error. The following table describes how to update these syntaxes.

Errors	Use Instead
repmat(A,r1,r2), where r1 and r2 are row vectors	repmat(A,[r1 r2])
repmat(A,empt), where empt is an empty array	repmat(A,1)
repmat(A,empt1,empt2), where empt1 and empt2 are empty arrays	repmat(A,1)
repmat(A,n,empt), where n is an integer and empt is an empty array	repmat(A,[n 1])