cotd
Cotangent of argument in degrees
Syntax
Description
Examples
Cotangent of Angles Approaching 90 and 180 Degrees
Create a vector of input angles consisting of 90° and the next smaller and larger double precision numbers. Then compute the cotangent.
x1 = [90-eps(90) 90 90+eps(90)]; y1 = cotd(x1)
y1 = 1×3
10-15 ×
0.2480 0 -0.2480
cotd
returns zero when the input angle is exactly 90°. Evaluation at the next smaller double-precision angle returns a slightly positive result. Likewise, the cotangent is slightly negative when the input angle is the next double-precision number larger than 90.
The behavior is similar for input angles near 180°.
x2 = [180-eps(180) 180 180+eps(180)]; y2 = cotd(x2)
y2 = 1×3
1015 ×
-2.0159 -Inf 2.0159
Cotangent of Complex Angle, Specified in Degrees
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 cotd
operation is element-wise when X
is nonscalar.
Data Types: single
| double
| table
| timetable
Complex Number Support: Yes
Output Arguments
Y
— Cotangent of angle
scalar value | vector | matrix | multidimensional array | table | timetable
Cotangent 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
cotd
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 cotd
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 cotd
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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