realpow
Array power for real-only output
Syntax
Z = realpow(X,Y)
Description
raises each element of array Z
= realpow(X
,Y
)X
to the power of its corresponding
element in array Y
. Arrays X
and
Y
must be the same size or be compatible. The range of realpow
is the set of all real
numbers, i.e., all elements of the output array Z
must be
real.
If either X
or
Y
is a table or timetable, then Z
is a table
or timetable. (since R2023a)
Examples
Powers of Matrix Elements
Create a 3-by-3 matrix with the same value in each element.
X = -2*ones(3,3)
X = 3×3
-2 -2 -2
-2 -2 -2
-2 -2 -2
Compute a 3-by-3 matrix of integer values.
Y = pascal(3)
Y = 3×3
1 1 1
1 2 3
1 3 6
Compute the element-wise powers of the elements in X
corresponding to the exponents defined in Y
.
Z = realpow(X,Y)
Z = 3×3
-2 -2 -2
-2 4 -8
-2 -8 64
Input Arguments
X
, Y
— Operands
scalars | vectors | matrices | multidimensional arrays | tables | timetables
Operands, specified as scalars, vectors, matrices, multidimensional
arrays, tables, or timetables. X
and Y
must either be the same size or have sizes that are compatible (for example,
X
is an M
-by-N
matrix and Y
is a scalar or
1
-by-N
row vector). For more
information, see Compatible Array Sizes for Basic Operations.
The values in X
and Y
must be real.
If X
and Y
are of integer data types,
then the values of Y
must also be nonnegative
integers.
Data Types: single
| double
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
| logical
| char
| table
| timetable
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
The
realpow
function fully supports tall arrays. For more information,
see Tall Arrays.
C/C++ Code Generation
Generate C and C++ code using MATLAB® 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 realpow
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 R2006aR2023a: Perform calculations directly on tables and timetables
The realpow
function can calculate on all variables within a table or
timetable without indexing to access those variables. All variables must have data types
that support the calculation. For more information, see Direct Calculations on Tables and Timetables.
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