atand

Inverse tangent in degrees

Syntax

Y = atand(X)

Description

Y = atand(X) returns the inverse tangent (tan^-1) of the elements of X in degrees. The function accepts both real and complex inputs.

• For real values of X, atand(X) returns values in the interval [-90, 90].

• For complex values of X, atand(X) returns complex values.

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

atand(10+i)

ans = 
84.3450 + 0.5618i

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 R2006a

R2023a: 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.