realsqrt
Square root for nonnegative real arrays
Syntax
Description
returns the square root of each element of array Y
= realsqrt(X
)X
. The size of
Y
is the same as the size of X
.
If you want negative and complex numbers to return complex results instead of
error messages, then use sqrt
instead.
If X
is a table or
timetable, then Y
is a table or timetable. (since R2023a)
Examples
Square Root of Matrix Elements
Create a 4-by-4 matrix of real, positive values.
X = magic(4)
X = 4×4
16 2 3 13
5 11 10 8
9 7 6 12
4 14 15 1
Compute the square root of each element in X
.
Y = realsqrt(X)
Y = 4×4
4.0000 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
X
— Input
scalar | vector | matrix | multidimensional array | table | timetable
Input, specified as a scalar, vector, matrix, multidimensional array,
table, or timetable. The values in X
must be nonnegative
and real.
Data Types: single
| double
| table
| timetable
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
The
realsqrt
function fully supports tall arrays. For more information,
see Tall 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, 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 realsqrt
function
supports GPU array input with these 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, see Work with Complex Numbers on a GPU (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 realsqrt
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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