flip

Flip order of elements

Syntax

B = flip(A)

B = flip(A,dim)

Description

B = flip(A) returns array B the same size as A, but with the order of the elements reversed. The dimension that is reordered in B depends on the shape of A:

• If A is vector, then flip(A) reverses the order of the elements along the length of the vector.

• If A is a matrix, then flip(A) reverses the elements in each column.

• If A is an N-D array, then flip(A) operates on the first dimension of A in which the size value is not 1.

B = flip(A,dim) reverses the order of the elements in A along dimension dim. For example, if A is a matrix, then flip(A,1) reverses the elements in each column, and flip(A,2) reverses the elements in each row.

Examples

Flip Character Vector

A = 'no word, no bond, row on.';
B = flip(A)

B = 
'.no wor ,dnob on ,drow on'

Flip Column Vector

A = [1;2;3];
B = flip(A)

B = 3×1

     3
     2
     1

Flip Matrix

Create a diagonal matrix, A.

A = diag([100 200 300])

A = 3×3

   100     0     0
     0   200     0
     0     0   300

Flip A without specifying the dim argument.

B = flip(A)

B = 3×3

     0     0   300
     0   200     0
   100     0     0

Now, flip A along the second dimension.

B = flip(A,2)

B = 3×3

     0     0   100
     0   200     0
   300     0     0

Flip N-D Array

Create a 1-by-3-by-2 array.

A = zeros(1,3,2);
A(:,:,1) = [1 2 3];
A(:,:,2) = [4 5 6];
A

A = 
A(:,:,1) =

     1     2     3


A(:,:,2) =

     4     5     6

Flip A without specifying the dim argument.

B = flip(A)

B = 
B(:,:,1) =

     3     2     1


B(:,:,2) =

     6     5     4

Now, flip A along the third dimension.

B = flip(A,3)

B = 
B(:,:,1) =

     4     5     6


B(:,:,2) =

     1     2     3

Flip Cell Array

Create a 3-by-2 cell array.

A = {'foo',1000; 999,true; 'aaa','bbb'}

A=3×2 cell array
    {'foo'}    {[1000]}
    {[999]}    {[   1]}
    {'aaa'}    {'bbb' }

Flip A without specifying the dim argument.

B = flip(A)

B=3×2 cell array
    {'aaa'}    {'bbb' }
    {[999]}    {[   1]}
    {'foo'}    {[1000]}

Now, flip A along the second dimension.

B = flip(A,2)

B=3×2 cell array
    {[1000]}    {'foo'}
    {[   1]}    {[999]}
    {'bbb' }    {'aaa'}

Input Arguments

A — Input array

vector | matrix | multidimensional array | table | timetable

Input array, specified as a vector, matrix, multidimensional array, table, or timetable.

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

Example: [1 2 3 4]

Example: ['abcde']

Example: [1 2; 3 4]

Example: {'abcde',[1 2 3]}

Example: table(rand(1,5),rand(1,5))

dim — Dimension to operate along

positive integer scalar

Dimension to operate along, specified as a positive integer scalar. If you do not specify the dimension, then the default is the first array dimension whose size does not equal 1.

Consider an m-by-n input matrix, A:

• flip(A,1) reverses the order of the elements in each column of A and returns an m-by-n matrix.

• flip(A,2) reverses the order of the elements in each row of A and returns an m-by-n matrix.

Extended Capabilities

Tall Arrays

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

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

• If specified, the dim argument must be greater than 1.

For more information, see Tall Arrays.

C/C++ Code Generation

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

Usage notes and limitations:

• Does not support cell arrays for the first argument.

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 flip 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 in R2013b