numpy.tanh () in Python

Equivalent to np.sinh (x) / np.cosh (x) or -1j * np.tan (1j * x) .

Parameters:

array: [array_like] elements are in radians.
2pi Radians = 36o degrees

Return: An array with hyperbolic tangent of x for all x ie array elements

Code # 1: Work

# Python3 program explaining
# tanh () function

 

import numpy as np

import math

 

in_array = [ 0 , math.pi / 2 , np.pi / 3 , np.pi]

print ( "Input array:" , in_array)

 

tanh_Values ​​ = np.tanh (in_array)

print ( "Tangent Hyperbolic values:" , tanh_Values)

Output:

 Input array: [0, 1.5707963267948966, 1.0471975511965976, 3.141592653589793] Tangent Hyperbolic values: [0. 0.91715234 0.78071444 0.99627208] 

Code # 2: Graphic view

# Python program displaying the graphic
# representation of the tanh function ( )

import numpy as np

import matplotlib.pyplot as plt

 

in_array = np.linspace ( - np.pi, np.pi, 12 )

out_array = np.tanh ( in_array)

 

print ( "in_ array: " , in_array)

print ( "out_array:" , out_array)

 
# red for numpy.tanh ()

plt.plot (in_array , out_array, color = `red` , marker = "o" )

plt.title ( "numpy.tanh ()" )

plt.xlabel ( "X" )

plt.ylabel ( "Y" )

plt.show ()

< strong> Output:

 in_array: [-3.14159265 -2.57039399 -1.99919533 -1.42799666 -0.856798 -0.28559933 0.28559933 0.856798 1.42799666 1.99919533 2.57039399 3.14159265] out_array: [-0.990.99 -0.27807943 0.27807943 0.69460424 0.89125532 0.96397069 0.98836197 0.99627208] 

Links: https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.tanh.html#numpy.tanh
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