Compute the natural logarithm of one plus each element in floating-point accuracy Using NumPy
Last Updated :
02 Sep, 2020
Let’s see the program for computing the natural logarithm of one plus each element of a given array in floating-point accuracy using NumPy library.
For doing this task we are using numpy.log1p() function of NumPy. This function returns the array of natural logarithm of one plus each element of the input array.
Syntax: numpy.log1p(arr, out = None, *, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None, ufunc ‘log1p’)
Now, let’s see an example:
Example 1:
Python3
import numpy as np
arr = np.array([ 1e - 90 , 1e - 100 ])
rslt = np.log1p(arr)
print (rslt)
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Output:
[1.e-090 1.e-100]
Example 2:
Python3
import numpy as np
arr = np.array([ 1 , 2 , 3 , 4 ])
rslt = np.log1p(arr)
print (rslt)
|
Output:
[0.69314718 1.09861229 1.38629436 1.60943791]
Example 3:
Python3
import numpy as np
arr = np.array([ 1 , 1e - 1 , 3 , 1e - 0 ])
rslt = np.log1p(arr)
print (rslt)
|
Output:
[0.69314718 0.09531018 1.38629436 0.69314718]
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