log() in Python. The numpy. log() is a mathematical function that helps user to calculate Natural logarithm of x where x belongs to all the input array elements. Natural logarithm log is the inverse of the exp(), so that log(exp(x)) = x.
Numpy seems to take a cue from MATLAB/Octave and uses log to be "log base e" or ln . Also like MATLAB/Octave, Numpy does not offer a logarithmic function for an arbitrary base.
How to Use Python math to Calculate the Natural Logarithm (ln) The Python library, math , comes with a function called log() . The function takes two parameters: The value that you want to calculate the logarithm for, and.
np.log
is ln
, whereas np.log10
is your standard base 10 log.
Correct, np.log(x)
is the Natural Log (base e
log) of x
.
For other bases, remember this law of logs: log-b(x) = log-k(x) / log-k(b)
where log-b
is the log in some arbitrary base b
, and log-k
is the log in base k
, e.g.
here k = e
l = np.log(x) / np.log(100)
and l
is the log-base-100 of x
I usually do like this:
from numpy import log as ln
Perhaps this can make you more comfortable.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With