secd

Secant of argument in degrees

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Syntax

Y = secd(X)

Description

Y = secd(X) returns the secant of the elements of X, which are expressed in degrees.

example

Examples

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Secant of 90 Degrees Compared to Secant of π/2 Radians

Open Live Script

secd(90)

ans = 
Inf

sec(pi/2)

ans = 
1.6331e+16

secd(90) is infinite, whereas sec(pi/2) is large but finite.

Secant of Vector of Complex Angles, Specified in Degrees

Open Live Script

z = [35+i 15+2i 10+3i];
y = secd(z)

y = 1×3 complex

   1.2204 + 0.0149i   1.0346 + 0.0097i   1.0140 + 0.0094i

Input Arguments

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`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 secd operation is element-wise when X is nonscalar.

Data Types: single | double | table | timetable
Complex Number Support: Yes

Output Arguments

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`Y` — Secant of angle
scalar value | vector | matrix | multidimensional array | table | timetable

Secant 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 secd 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^® returns Inf.
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 secd 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 R2006a

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R2023a: Perform calculations directly on tables and timetables

The secd 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.

secd

Syntax

Description

Examples

Secant of 90 Degrees Compared to Secant of π/2 Radians

Secant of Vector of Complex Angles, Specified in Degrees

Input Arguments

X — Angle in degrees scalar value | vector | matrix | multidimensional array | table | timetable

Output Arguments

Y — Secant of angle scalar value | vector | matrix | multidimensional array | table | timetable

Extended Capabilities

Tall Arrays Calculate with arrays that have more rows than fit in memory.

C/C++ Code Generation Generate C and C++ code using MATLAB® Coder™.

Thread-Based Environment Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

GPU Arrays Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Distributed Arrays Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

Version History

R2023a: Perform calculations directly on tables and timetables

See Also

`X` — Angle in degrees
scalar value | vector | matrix | multidimensional array | table | timetable

`Y` — Secant of angle
scalar value | vector | matrix | multidimensional array | table | timetable

Tall Arrays
Calculate with arrays that have more rows than fit in memory.

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Thread-Based Environment
Run code in the background using MATLAB® `backgroundPool` or accelerate code with Parallel Computing Toolbox™ `ThreadPool`.

GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.