pagetranspose
Syntax
Description
Examples
Transpose Pages of N-D Array
Create a 3-D array A
, and then use pagetranspose
to transpose each page of the array.
r = repelem(1:3,3,1); A = cat(3,r,2*r,3*r)
A = A(:,:,1) = 1 2 3 1 2 3 1 2 3 A(:,:,2) = 2 4 6 2 4 6 2 4 6 A(:,:,3) = 3 6 9 3 6 9 3 6 9
B = pagetranspose(A)
B = B(:,:,1) = 1 1 1 2 2 2 3 3 3 B(:,:,2) = 2 2 2 4 4 4 6 6 6 B(:,:,3) = 3 3 3 6 6 6 9 9 9
Input Arguments
X
— Input array
multidimensional array
Input array, specified as a multidimensional array.
Data Types: single
| double
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
| logical
| char
| string
| struct
| cell
| categorical
| datetime
| duration
| calendarDuration
Complex Number Support: Yes
More About
Array Pages
Page-wise functions like pagetranspose
operate on 2-D
matrices that have been arranged into a multidimensional array. For example, the elements in
the third dimension of a 3-D array are commonly called pages because
they stack on top of each other like pages in a book. Each page is a matrix that the
function operates on.
You can also assemble a collection of 2-D matrices into a higher dimensional array, like a 4-D
or 5-D array, and in these cases pagetranspose
still treats the
fundamental unit of the array as a 2-D matrix that the function operates on, such as
X(:,:,i,j,k,l)
.
The cat
function is useful for assembling a
collection of matrices into a multidimensional array, and the zeros
function is useful for preallocating a multidimensional array.
Tips
The page-wise transpose is equivalent to permuting the first two dimensions of the array with
permute(X,[2 1 3:ndims(X)])
.
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Usage notes and limitations:
Code generation does not support cell arrays for this function.
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 pagetranspose
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 R2020b
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