realsqrt

Square root for nonnegative real arrays

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Syntax

Y = realsqrt(X)

Description

example

Y = realsqrt(X)returns the square root of each element of arrayX. The size ofYis the same as the size ofX.

If you want negative and complex numbers to return complex results instead of error messages, then usesqrtinstead.

Examples

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Open Live Script

Create a 4-by-4 matrix of real, positive values.

X = magic(4)

X =4×416 2 3 13 5 11 10 8 9 7 6 12 4 14 15 1

Compute the square root of each element inX.

Y = realsqrt(X)

Y =4×44.0000 1.4142 1.7321 3.6056 2.2361 3.3166 3.1623 2.8284 3.0000 2.6458 2.4495 3.4641 2.0000 3.7417 3.8730 1.0000

Input Arguments

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`X`—Input matrix
scalar|vector|matrix|multidimensional array

Input matrix, specified as a scalar, vector, matrix, or multidimensional array. The values inXmust be nonnegative and real.

Data Types:single|double

Extended Capabilities

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

This function fully supports tall arrays. For more information, seeTall Arrays.

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU 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, seeRun MATLAB Functions in Thread-Based Environment.

GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Usage notes and limitations:

If the output of the function running on the GPU can be complex, then you must explicitly specify its input arguments as complex. For more information, seeWork with Complex Numbers on a GPU(Parallel Computing Toolbox).

For more information, seeRun 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, seeRun MATLAB Functions with Distributed Arrays(Parallel Computing Toolbox).

Version History

Introduced before R2006a

realsqrt

Syntax

Description

Examples

的平方根矩阵的元素s

Input Arguments

X—Input matrixscalar|vector|matrix|multidimensional array

Extended Capabilities

Tall ArraysCalculate with arrays that have more rows than fit in memory.

C/C++ Code GenerationGenerate C and C++ code using MATLAB® Coder™.

GPU Code GenerationGenerate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Thread-Based EnvironmentRun code in the background using MATLAB®backgroundPoolor accelerate code with Parallel Computing Toolbox™ThreadPool.

GPU ArraysAccelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Distributed ArraysPartition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.