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.
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
# 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) |
Output :
Input array : [1, 3, 5] Output array : [ 0.69314718 1.38629436 1.79175947]
Code 2 : Graphical representation
# 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() |
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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