tanh()

import math
print(math.tanh(-5))    # -0.9999092042625951
print(math.tanh(-1))    # -0.7615941559557649
print(math.tanh(-0.9))  # -0.7162978701990244
print(math.tanh(0))     # 0.0
print(math.tanh(0.9))   # 0.7162978701990244
print(math.tanh(1))     # 0.7615941559557649
print(math.tanh(5))     # 0.9999092042625951

Inputs in degree

import math
in_degree = 50
in_redian = math.radians(in_degree)
print(math.tanh(in_redian)) # 0.7027254303610717

Drawing graph of tanh()

import matplotlib.pyplot as plt
x=[]
y=[]
i=-10
while (i<=10):
    x.append(i)
    y.append(math.tanh(i))
    i=i+0.1
plt.plot(x,y)
plt.axvline(x=0.00,linewidth=2, color='#f1f1f1')
plt.axhline(y=0.00,linewidth=2, color='#f1f1f1')
plt.grid(linestyle='-',
    linewidth=0.5,color='#f1f1f1')
plt.show()

Example 1: Using tanh() as an Activation Function

import math
inputs = [-2, -1, 0, 1, 2]
outputs = [math.tanh(x) for x in inputs]
print(outputs)  # Outputs between -1 and 1

Example 2: Using cmath.tanh() for Complex Numbers

import cmath
z = 2 + 3j
print(cmath.tanh(z))  # Outputs tanh for a complex number

(0.965385879022133-0.009884375038322495j)

Example 3: Comparing tanh() with sinh() and cosh()

import math
x = 1.0
tanh_val = math.tanh(x)
sinh_cosh_val = math.sinh(x) / math.cosh(x)
print(f"tanh(1.0) = {tanh_val}")
print(f"sinh(1.0) / cosh(1.0) = {sinh_cosh_val}")

tanh(1.0) = 0.7615941559557649
sinh(1.0) / cosh(1.0) = 0.7615941559557649

Example 4: Limiting Hyperbolic Tangent Output

import math
x = 100  # Large input
print(math.tanh(x))  # Output will approach 1 as x increases
print(math.tanh(-100))  # Output will approach -1 as x decreases

Example 5: Using tanh() in a Mathematical Expression

import math
x = 0.5
y = 2.0
result = 3 * math.tanh(x) + 2 * math.tanh(y)
print(result) # output:  3.314406631931663

Subhendu Mohapatra

Author & Instructor at plus2net

I write and maintain practical tutorials on Python, PHP, SQL, JavaScript, HTML, jQuery, and web development at plus2net. The tutorials focus on clear explanations, working examples, and code that readers can test and adapt while learning.

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