atand
Inverse tangent in degrees
Syntax
Description
Examples
Inverse Tangent of Vector
x = [-50 -20 0 20 50]; y = atand(x)
y = 1×5
-88.8542 -87.1376 0 87.1376 88.8542
The atand
operation is element-wise when you pass a vector, matrix, or N-D array.
Inverse Tangent of Complex Value
Input Arguments
X
— Tangent of angle
scalar value | vector | matrix | multidimensional array | table | timetable
Tangent of angle, specified as a real-valued or complex-valued scalar, vector, matrix,
multidimensional array, table, or timetable. The atand
operation is element-wise when X
is non-scalar.
Data Types: single
| double
| table
| timetable
Complex Number Support: Yes
Output Arguments
Y
— Angle in degrees
scalar value | vector | matrix | multidimensional array | table | timetable
Angle in degrees, returned as a real-valued or complex-valued scalar, vector, matrix,
multidimensional array, table, or timetable of the same size as
X
.
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
The
atand
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 atand
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 atand
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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