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.

example

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.

example

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

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Initialize Matrix with Same Element Value

Open Live Script

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

A = repmat(10,3,2)

Square Block Format

Open Live Script

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

Open Live Script

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

Open Live Script

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

A = [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

Open Live Script

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

Open Live Script

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

Open Live Script

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.

Input Arguments

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`A` — Input array
scalar | vector | matrix | multidimensional array

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

`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.

`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.

`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.

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))`

Compatibility Considerations

expand all

Some repetition arguments produce error

Behavior changed in R2019b

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])`

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 Verilog and VHDL code for FPGA and ASIC designs using HDL Coder™.

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

This function fully supports GPU arrays. 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).

Documentation

repmat

Syntax

Description

Examples

Initialize Matrix with Same Element Value

Square Block Format

Rectangular Block Format

3-D Block Array

Vertical Stack of Row Vectors

Horizontal Stack of Column Vectors

Tabular Block Format

Input Arguments

`A` — Input array
scalar | vector | matrix | multidimensional array

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

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

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

Tips

Compatibility Considerations

Some repetition arguments produce error

Extended Capabilities

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

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

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

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

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

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

See Also

MATLAB Documentation

Support

Documentation

repmat

Syntax

Description

Examples

Initialize Matrix with Same Element Value

Square Block Format

Rectangular Block Format

3-D Block Array

Vertical Stack of Row Vectors

Horizontal Stack of Column Vectors

Tabular Block Format

Input Arguments

A — Input array scalar | vector | matrix | multidimensional array

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

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

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

Tips

Compatibility Considerations

Some repetition arguments produce error

Extended Capabilities

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

C/C++ Code Generation Generate C and C++ code using MATLAB® Coder™.

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

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

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

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

See Also

MATLAB Documentation

Support

`A` — Input array
scalar | vector | matrix | multidimensional array

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

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

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

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

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

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

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

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

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