Logs in NumPy
NumPy provides built-in functions to compute logarithms with bases 2, e
(natural log), and 10. Additionally, you can create a custom function to
compute logarithms with any base.
Note: If the logarithm cannot be computed for certain elements, NumPy will
return -inf or inf.
Logarithm with Base 2
Use the np.log2() function to compute the base-2 logarithm of array
elements.
Program:
import numpy as np
arr = np.arange(1, 10) # Creates an array from 1 to 9
print(np.log2(arr))
Output:
[0. 1.
1.5849625 2. 2.32192809
2.5849625
2.80735492 3. 3.169925
]
Logarithm with Base 10
Use the np.log10() function for base-10 logarithms.
Program:
import numpy as np
arr = np.arange(1, 10)
print(np.log10(arr))
Output:
[0. 0.30103 0.47712125
0.60205999 0.69897 0.77815125
0.84509804 0.90308999 0.95424251]
Natural Logarithm (Base e)
For natural logarithms (base e), use np.log().
Program:
import numpy as np
arr = np.arange(1, 10)
print(np.log(arr))
Output:
[0. 0.69314718 1.09861229 1.38629436
1.60943791 1.79175947
1.94591015 2.07944154 2.19722458]
Logarithm with Any Base
NumPy doesn’t provide a direct function for arbitrary bases. However, you
can use np.frompyfunc() along with Python’s built-in math.log() to create a
custom universal function (ufunc).
Program:
from math import log
import numpy as np
nplog = np.frompyfunc(log, 2, 1)
# 2 inputs (value and base), 1 output
print(nplog(100, 15))
# Log of 100 with base 15
Output:
1.7005483074552052
More topic in Numpy
