Hyperbolic Functions

This is a detailed tutorial of the NumPy Hyperbolic Universal Functions. Learn the usage of these functions with the help of examples.

Table of Contents

These are those function which takes value in the radians ad will give us alternative values for sin, cos and tan. The Unfuncs provide us with sinh(), cosh() and tanh() the functions which help in this process. These are very helpful in explaining various real-life curves.

Let us take an example:

#first we will import the numpy package 
import numpy as np
#now in the next step we use sinh() function
a=np.sinh(np.pi/4)
#now we will print the result
print(a)

Output.

0.868670961486

Now let us take an example where we will find the hyperbolic values for elements in the array:

#first we will import the numpy package 
import numpy as np
#now in the next step we use sinh() function
a=np.array([np.pi/4,np.pi/1,np.pi/7,np.pi/6])
b=np.sinh(a)
#now we will print the result
print(b)

Output.

[ 0.86867096 11.54873936 0.46401763 0.54785347]

Finding Angles

In order to find angles form the values of hyperbolic sin, cos, tan, we need to have the inverse of these values. In NumPy, we have some Unfuncs which help us getting the radians’ values for these. These functions are as follow. arcsinh(), arccosh() and arctanh().

Let us take an example to understand it better:

#first we will import the numpy package 
import numpy as np
#now in the next step we use arcsinh() function
a=np.arcsinh(np.pi/4)
#now we will print the result
print(a)

Output.

0.721225488727

we will take another example to find for cosh and tanh:

#first we will import the numpy package 
import numpy as np
#now in the next step we use arccosh() function
a=np.arccosh(1.0)
#now we will print the result
print(a)

Output.

0.0

Another example:

#first we will import the numpy package 
import numpy as np
#now in the next step we use arctanh() function
a=np.arctanh(0.5)
#now we will print the result
print(a)

Output.

0.549306144334

Angles of Values

In order to find the angles of the values which we pass in an array, let us take an example to understand this concept.

#first we will import the numpy package 
import numpy as np
#now in the next step we use arcsinh() function
a=np.array([0.2,0.5])
b=np.arcsinh(a)
#now we will print the result
print(b)

Output.

[ 0.19869011 0.48121183]

I hope you found this guide useful. If so, do share it with others who are willing to learn Numpy and Python. If you have any questions related to this article, feel free to ask us in the comments section.

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