acsc

Inverse cosecant in radians

Syntax

Y = acsc(X)

Description

Y = acsc(X) returns the Inverse Cosecant (csc^-1) of the elements of X in radians. The function accepts both real and complex inputs.

• For real values of X in the intervals [-∞, -1] and [1, ∞], acsc(X) returns real values in the interval [-π/2, π/2].

• For real values of X in the interval (-1, 1) and for complex values of X, acsc(X) returns complex values.

Examples

Inverse Cosecant of a Value

Find the inverse cosecant of a value.

acsc(3)

ans = 0.3398

Inverse Cosecant of a Vector of Complex Angles

Find the inverse cosecant of the elements of vector x. The acsc function acts on x element-wise.

x = [0.5i 1+3i -2.2+i];
Y = acsc(x)

Y = 1×3 complex

   0.0000 - 1.4436i   0.0959 - 0.2970i  -0.3795 - 0.1833i

Plot the Inverse Cosecant Function

Plot the inverse cosecant function over the intervals $$-10\le x<-1$$ and $$1<x\le 10$$.

x1 = -10:0.01:-1.01; 
x2 = 1.01:0.01:10;
plot(x1,acsc(x1),'b')
hold on
plot(x2,acsc(x2),'b')
grid on

Input Arguments

X — Cosecant of angle

scalar | vector | matrix | multidimensional array

Cosecant of angle, specified as a scalar, vector, matrix, or multidimensional array. The acsc operation is element-wise when X is nonscalar.

Data Types: single | double
Complex Number Support: Yes

More About

Inverse Cosecant

The inverse cosecant is defined as

$${\csc }^{-1}(z)={\sin }^{-1}\left(\frac{1}{z}\right).$$

Extended Capabilities

Tall Arrays

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

This function fully supports tall arrays. For more information, see Tall Arrays.

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

GPU Arrays

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

Usage notes and limitations:

• If the output of the function running on the GPU can be complex, then you must explicitly specify its input arguments as complex. For more information, see Work with Complex Numbers on a GPU (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).