realpow

Array power for real-only output

Syntax

Z = realpow(X,Y)

Description

Z = realpow(X,Y) raises each element of array 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

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Powers of Matrix Elements

Open Live Script

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

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`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.

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 R2006a

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R2023a: 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.

realpow

Syntax

Description

Examples

Powers of Matrix Elements

Input Arguments

X, Y — Operands scalars | vectors | matrices | multidimensional arrays | tables | timetables

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™.

Thread-Based Environment Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

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™.