numpy.log10 () in Python

Parameters :

  array:  [array_like] Input array or object.  out:  [ndarray, optional] Output array with same dimensions as Input array, placed with result.  ** kwargs:  allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function.  where:  [array_like, optional] True value means to calculate the universal functions (ufunc) at that position, False value means to leave the value in the output alone. 

Return:

 An array with Base-10 logarithmic value of x; where x belongs to all elements of input array. 

Code 1: Working

# Python program explaining
# log10 () function

 

import numpy as np

 

in_array = [ 1 , 3 , 5 , 10 * * 8 ]

print ( "Input array:" , i n_array)

 

out_array = np.log10 (in_array)

print ( "Output array:" , out_array)

 

 

print ( "np.log10 (4 ** 4):" , np. log10 ( 100 * * 4 ))

print ( "np.log10 (2 ** 8):" , np.log10 ( 10 * * 8 ))

Output:

 Input array: [1, 3, 5, 100000000] Output array: [0. 0.47712125 0.69897 8.] np.log10 (4 ** 4): 8.0 np.log10 (2 ** 8): 8.0 

Code 2: Graphical representation

Out:

 out_array: [0. 0.30103 0.47712125 0.60205999 0.69897] 

Links:
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.log10.html # numpy.log10
,


# Show Python program
# Graphical view
# log10 () function

 

import numpy as np

import matplotlib.pyplot as plt

 

in_array = [ 1 , 2 , 3 , 4 , 5 ]

out_array = np.log10 (in_array)

  

print ( "out_array:" , out_array)

 

plt.plot (in_array, in_array, color = ` blue` , marker = "*" )

 
# red for numpy.log10 ()

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

plt.title ( "numpy.log10 ()" )

plt.xlabel ( " out_array " )

plt.ylabel ( " in_array " )

plt.show ()