deg2rad
Convert angle from degrees to radians
Syntax
Description
Examples
Right Angle in Radians
Surface Distance
Specify the spherical distance between Munich and Bangalore in degrees and the mean radius of Earth in kilometers. Compute the distance (measured along the Earth's surface) between Munich and Bangalore, in kilometers.
D = 64.7; radEarth = 6371; R = deg2rad(D); dist = radEarth*R
dist = 7.1943e+03
Input Arguments
D
— Angle in degrees
scalar | vector | matrix | multidimensional array
Angle in degrees, specified as a scalar, vector, matrix, or
multidimensional array. If D
contains complex elements, deg2rad
converts
the real and imaginary parts separately.
Data Types: single
| double
Complex Number Support: Yes
Output Arguments
R
— Angle in radians
scalar | vector | matrix | multidimensional array
Angle in radians, returned as a scalar, vector, matrix, or multidimensional
array. R
is the same size as D
.
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
The
deg2rad
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 deg2rad
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 in R2015b
See Also
MATLAB Command
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