atan2d
Four-quadrant inverse tangent in degrees
Syntax
Description
D = atan2d(
returns
the four-quadrant
inverse tangent (tan-1) of Y
,X
)Y
and X
,
which must be real. The result, D
, is expressed
in degrees.
Examples
Inverse Tangent of Four Points on the Unit Circle
Input Arguments
Y
— y-coordinates
scalar | vector | matrix | multidimensional array | table | timetable
y-coordinates, specified as a scalar, vector, matrix, multidimensional
array, table, or timetable. Inputs Y
and
X
must either be the same size or have sizes that are
compatible (for example, Y
is an
M
-by-N
matrix and
X
is a scalar or
1
-by-N
row vector). For more
information, see Compatible Array Sizes for Basic Operations.
Data Types: single
| double
| table
| timetable
X
— x-coordinates
scalar | vector | matrix | multidimensional array | table | timetable
x-coordinates, specified as a scalar, vector, matrix, multidimensional
array, table, or timetable. Inputs Y
and
X
must either be the same size or have sizes that are
compatible (for example, Y
is an
M
-by-N
matrix and
X
is a scalar or
1
-by-N
row vector). For more
information, see Compatible Array Sizes for Basic Operations.
Data Types: single
| double
| table
| timetable
More About
Four-Quadrant Inverse Tangent
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
The
atan2d
function fully supports tall arrays. For more information,
see Tall Arrays.
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Usage notes and limitations:
If you use
atan2d
with single type and double type operands, the generated code might not produce the same result as MATLAB®. See Binary Element-Wise Operations with Single and Double Operands (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 atan2d
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 R2012bR2023a: Perform calculations directly on tables and timetables
The atan2d
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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