tand
Tangent of argument in degrees
Syntax
Description
Examples
Tangent of 90 Degrees Compared to Tangent of π/2 Radians
tand(90)
ans = Inf
tan(pi/2)
ans = 1.6331e+16
tand(90)
is infinite, whereas tan(pi/2)
is large but finite.
Tangent of Vector of Complex Angles, Specified in Degrees
z = [180+i 15+2i 10+3i]; y = tand(z)
y = 1×3 complex
0.0000 + 0.0175i 0.2676 + 0.0374i 0.1758 + 0.0539i
Input Arguments
X
— Angle in degrees
scalar value | vector | matrix | multidimensional array | table | timetable
Angle in degrees, specified as a real-valued or complex-valued scalar, vector, matrix,
multidimensional array, table, or timetable. The tand
operation is element-wise when X
is nonscalar.
Data Types: single
| double
| table
| timetable
Complex Number Support: Yes
Output Arguments
Y
— Tangent of angle
scalar value | vector | matrix | multidimensional array | table | timetable
Tangent of angle, 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
tand
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:
In some cases, generated code returns
-Inf
when MATLAB® returnsInf
.In some cases, generated code returns
Inf
when MATLAB returns-Inf
.
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 tand
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 tand
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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