paddata
Description
pads B
= paddata(A
,m
)A
to size m
by adding elements to the trailing
side of A
. For example, for a scalar size m
:
If
A
is a vector, thenpaddata(A,m)
padsA
to lengthm
.If
A
is a matrix, table, or timetable, thenpaddata(A,m)
padsA
to havem
rows.If
A
is a multidimensional array, thenpaddata(A,m)
padsA
to the size specified bym
along the first dimension whose size does not equal 1.
If m
is less than or equal to the size of A
in the
operating dimension, then paddata
returns all of
A
.
specifies additional parameters for padding using one or more name-value arguments. For
example, B
= paddata(A
,m
,Name=Value
)paddata(A,m,Pattern="circular")
pads by repeating the input data
circularly.
Examples
Pad Vector
Create a four-element column vector, and pad the vector to six elements. By default, the paddata
function adds zeros to the trailing size of the numeric vector.
A = [1; 3; 5; 7]; B = paddata(A,6)
B = 6×1
1
3
5
7
0
0
Pad a row vector to six elements.
A2 = [2 4 6 8]; B2 = paddata(A2,6)
B2 = 1×6
2 4 6 8 0 0
Match Length of Another Vector
Create two vectors with different lengths.
A1 = [2; 8; 3; 5]; A2 = [9; 4; 6; 2; 7; 7; 0];
Determine the length of the longer vector.
szA1 = size(A1,1); szA2 = size(A2,1); [m,idx] = max([szA1 szA2])
m = 7
idx = 2
Pad the shorter vector to match the length of the longer vector.
B1 = paddata(A1,m)
B1 = 7×1
2
8
3
5
0
0
0
You can concatenate vectors of the same length. Create a matrix using the two vectors.
C = [B1 A2]
C = 7×2
2 9
8 4
3 6
5 2
0 7
0 7
0 0
Pad Matrix
Create a 3-by-3 matrix. Pad the columns to a length of 4 by adding one element to each column. Pad the rows to a length of 6 by adding three elements to each row.
A = [1 3 5; 2 4 6; 7 8 10]
A = 3×3
1 3 5
2 4 6
7 8 10
B = paddata(A,[4 6])
B = 4×6
1 3 5 0 0 0
2 4 6 0 0 0
7 8 10 0 0 0
0 0 0 0 0 0
Add Array Page
Create a 3-by-3 matrix as the first page in a 3-D array. Add a second page to the array by padding along the third dimension.
A = [1 3 5; 2 4 6; 7 8 10]
A = 3×3
1 3 5
2 4 6
7 8 10
B = paddata(A,2,Dimension=3)
B = B(:,:,1) = 1 3 5 2 4 6 7 8 10 B(:,:,2) = 0 0 0 0 0 0 0 0 0
Specify Fill Values for Table Variables
Create a timetable with variables of different data types.
num = [10; 20; 30]; cat = categorical(["A"; "B"; "A"]); log = logical([1; 0; 1]); str = ["Text 1"; "Text 2"; "Text 3"]; TT = timetable(num,cat,log,str,Timestep=hours(2))
TT=3×4 timetable
Time num cat log str
____ ___ ___ _____ ________
0 hr 10 A true "Text 1"
2 hr 20 B false "Text 2"
4 hr 30 A true "Text 3"
Pad each timetable variable. paddata
uses the default fill value for the data type of each variable. The default fill value for each data type is the same as the value of elements that MATLAB® creates when assigning a value beyond the last row of the table.
B1 = paddata(TT,6)
B1=6×4 timetable
Time num cat log str
_____ ___ ___________ _____ _________
0 hr 10 A true "Text 1"
2 hr 20 B false "Text 2"
4 hr 30 A true "Text 3"
6 hr 0 <undefined> false <missing>
8 hr 0 <undefined> false <missing>
10 hr 0 <undefined> false <missing>
Specify a custom fill value for the elements to add to each timetable variable. paddata
extends the row times, so you do not need to specify a fill value for the row times.
B2 = paddata(TT,6,FillValue={mean(num),"C",1,""})
B2=6×4 timetable
Time num cat log str
_____ ___ ___ _____ ________
0 hr 10 A true "Text 1"
2 hr 20 B false "Text 2"
4 hr 30 A true "Text 3"
6 hr 20 C true ""
8 hr 20 C true ""
10 hr 20 C true ""
Repeat First Element
Create a column vector, and pad the vector by repeating the leading element.
A = [1; 3; 5; 7]; B = paddata(A,7,Pattern="edge",Side="leading")
B = 7×1
1
1
1
1
3
5
7
Input Arguments
A
— Input data
vector | matrix | multidimensional array | table | timetable | cell array | structure array
Input data, specified as a vector, matrix, multidimensional array, table, timetable, cell array, or structure array.
Note
If A
is a cell array, then paddata
changes the size of the entire array. It does not change the size of each cell in
the array. Use the cellfun
function to apply
paddata
to each cell in a cell array.
m
— Size of padded data along operating dimension
nonnegative integer scalar | vector of nonnegative integers
Size of padded data along operating dimension, specified as a nonnegative integer scalar or vector of nonnegative integers. Each element represents the size of the padded data in an operating dimension.
If
m
is greater than the size ofA
in the operating dimension, thenpaddata
adds elements.If
m
is less than or equal to the size ofA
in the operating dimension, thenpaddata
returns the input data without adding elements.
Name-Value Arguments
Specify optional pairs of arguments as
Name1=Value1,...,NameN=ValueN
, where Name
is
the argument name and Value
is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.
Example: B = paddata(A,m,Pattern="circular")
Dimension
— Dimensions to operate along
"auto"
(default) | positive integer scalar | vector of positive integers
Dimensions to operate along, specified as "auto"
, a positive
integer scalar, or a vector of positive integers. Each element represents a dimension
of the input data.
If Dimension
is "auto"
, then the operating
dimension depends on the input arguments:
If
m
is a scalar andA
is an array, then the operating dimension is the first dimension whose size does not equal 1.If
m
is a vector, then the operating dimensions are1:numel(m)
.If
A
is a table or timetable, then the operating dimension is1
, and operation is along each table or timetable variable separately.
FillValue
— Fill value
[]
(default) | scalar | cell array | scalar structure
Fill value for added elements, specified as a scalar, cell array, or scalar structure.
The default fill value for each class is the same as the value of elements that MATLAB® creates when assigning a value past the end of a vector. For example, the default fill value for numeric input data is 0.
If
A
is an array, then a scalarFillValue
indicates the value for all elements added toA
during padding.If
A
is a table or timetable, then a cell arrayFillValue
indicates a different fill value for elements added to each table or timetable variable. The number of cells in the cell array must match the number of table or timetable variables. IfA
is a table with row names, thenpaddata
extends the row names with the default row name, such asRowN
; it does not pad the row names usingFillValue
. IfA
is a timetable with row times, thenpaddata
extends the row times; it does not pad the row times usingFillValue
.If
A
is a structure array, then a scalar structureFillValue
indicates a different fill value for each field in the input data. The number and names of fields inFillValue
must match the number and names of fields in the input data.
If you specify FillValue
, you cannot specify
Pattern
.
Pattern
— Pattern for adding elements
"constant"
(default) | "edge"
| "circular"
| "flip"
| "reflect"
Pattern for adding elements, specified as one of the pattern names in the table.
The pattern is repeated until the resized data has size m
.
If
A
is a table with row names, thenpaddata
extends the row names with the default row name, such asRowN
; it does not add to the row names usingPattern
.If
A
is a timetable with row times, thenpaddata
extends the row times; it does not add to the row times usingPattern
.
If you specify Pattern
, you cannot specify
FillValue
.
This table lists the pattern names with a description and a sample of how each
pattern pads the input data A = [1 2 3]
.
Pattern Name | Description | Padded Data |
---|---|---|
"constant" | Pad data with the default value determined by the data type of
A . |
|
"edge" | Pad data by replicating the leading and trailing endpoints as constant fill values. |
|
"circular" | Pad data by repeating the input data circularly. |
|
"flip" | Pad data by flipping the input data symmetrically. Endpoints are duplicated. |
|
"reflect" | Pad data by reflecting the input data. Endpoints are not duplicated. |
|
Side
— Side of input data for padding
"trailing"
(default) | "leading"
| "both"
Side of input data for padding, specified as one of these values:
"trailing"
— PadA
with trailing elements."leading"
— PadA
with leading elements."both"
— PadA
on both sides. If the number of elements to add in the operating dimension is even, then pad the trailing and leading sides ofA
evenly. If the number of elements to add in the operating dimension is odd, then pad the remaining element on the trailing side ofA
.
Tips
paddata
only adds elements to the input data.paddata
is recommended if you do not want to remove elements from your data and you do not require the resized data to match the target size. If you require the resized data to respect the sizes inm
, then consider using theresize
function, which can also remove elements from your data.
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™. (since R2024b)
Usage notes and limitations:
Code generation supports these:
numeric
,logical
,char
,struct
,duration
,table
, andtimetable
.Sparse inputs are not supported.
If the input is a
table
ortimetable
, then the number of variables in the output table must remain constant during code generation.All string or character vector inputs must be constant during code generation.
The input argument
m
must have a fixed size.Empty values are allowed only for
numeric
,logical
, andchar
inputs.Using a default
FillValue
is not supported forstruct
inputs.Timetables with custom values for the
userDataproperty
are not supported.If you specify
dim
, then it must be a constant.See Variable-Sizing Restrictions for Code Generation of Toolbox Functions (MATLAB Coder).
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™. (since R2024a)
The paddata
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™. (since R2024a)
This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).
Version History
Introduced in R2023b
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