numpy.log1p() in Python
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.
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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() functionimport 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() functionimport numpy as npimport 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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