numpy.log1p() in Python
Last Updated :
29 Nov, 2018
numpy.log1p(arr, out = None, *, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None, ufunc ‘log1p’) :
This mathematical function helps user to calculate natural logarithmic value of x+1 where x belongs to all the input array elements.
log1p is reverse of exp(x) – 1.
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 natural logarithmic value of x + 1;
where x belongs to all elements of input array.
Code 1 : Working
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)
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Output :
Input array : [1, 3, 5]
Output array : [ 0.69314718 1.38629436 1.79175947]
Code 2 : Graphical representation
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 = "*" )
plt.plot(out_array, y, color = 'red' , marker = "o" )
plt.title( "numpy.log1p()" )
plt.xlabel( "X" )
plt.ylabel( "Y" )
plt.show()
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Output :
out_array : [ 0.69314718 0.78845736 0.87546874 0.95551145 1.02961942 1.09861229]
References :
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.exp.html
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