# Python program explaining
# log1p() function
import numpy as np
  
in_array = [1, 3, 5]
print ("Input array : ", in_array)
  
out_array = np.log1p(in_array)
print ("Output array : ", out_array)

Input array :  [1, 3, 5]
Output array :  [ 0.69314718  1.38629436  1.79175947]

# Python program showing
# Graphical representation of 
# log1p() 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.log1p(in_array)
  
print ("out_array : ", out_array)
  
y = [1, 1.2, 1.4, 1.6, 1.8, 2]
plt.plot(in_array, y, color = 'blue', marker = "*")
  
# red for numpy.log1xp()
plt.plot(out_array, y, color = 'red', marker = "o")
plt.title("numpy.log1p()")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()  

out_array :  [ 0.69314718  0.78845736  0.87546874  0.95551145  1.02961942  1.09861229]