Skip to content
Related Articles

Related Articles

numpy.log() in Python
  • Difficulty Level : Basic
  • Last Updated : 04 Dec, 2020
GeeksforGeeks - Summer Carnival Banner

The numpy.log() is a mathematical function that helps user to calculate Natural logarithm of x where x belongs to all the input array elements.
Natural logarithm log is the inverse of the exp(), so that log(exp(x)) = x. The natural logarithm is log in base e.

Syntax :numpy.log(x[, out] = ufunc ‘log1p’)
Parameters :

array : [array_like] Input array or object.
out : [ndarray, optional] Output array with same dimensions as Input array, placed with result.

Return :
An array with Natural logarithmic value of x; where x belongs to all elements of input array.

Code #1 : Working






# Python program explaining
# log() function
import numpy as np
  
in_array = [1, 3, 5, 2**8]
print ("Input array : ", in_array)
  
out_array = np.log(in_array)
print ("Output array : ", out_array)
  
  
print("\nnp.log(4**4) : ", np.log(4**4))
print("np.log(2**8) : ", np.log(2**8))

Output :

Input array :  [1, 3, 5, 256]
Output array :  [ 0.          1.09861229  1.60943791  5.54517744]

np.log(4**4) :  5.54517744448
np.log(2**8) :  5.54517744448

 
Code #2 : Graphical representation




# Python program showing
# Graphical representation  
# of log() function
import numpy as np
import matplotlib.pyplot as plt
  
in_array = [1, 1.2, 1.4, 1.6, 1.8, 2]
out_array = np.log(in_array)
  
print ("out_array : ", out_array)
  
plt.plot(in_array, in_array, 
         color = 'blue', marker = "*")
  
# red for numpy.log()
plt.plot(out_array, in_array, 
         color = 'red', marker = "o")
           
plt.title("numpy.log()")
plt.xlabel("out_array")
plt.ylabel("in_array")
plt.show() 

Output :

out_array :  [ 0.          0.18232156  0.33647224  0.47000363  0.58778666  0.69314718]


References : https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.log.html#numpy.log
.

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.

My Personal Notes arrow_drop_up
Recommended Articles
Page :