I know np.exp2(x) exists that calculates 2^x where x is a numpy array, however, I am looking for a method that does K^x where K is any arbitrary number.
Is there any elegant way of doing it rather than stretching out K to the shape of x and doing a piecewise exponent?
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@tel: The "piecewise" seems to make things more confusing rather than less.user2357112– user23571122018-11-22 08:24:14 +00:00Commented Nov 22, 2018 at 8:24
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2 Answers
Just use the standard Python exponentiation operator **:
K**x
For example, if you have:
x = np.array([1,2,3])
K = 3
print(K**x)
The output is:
[ 3 9 27]
Notes
For Python classes, the behavior of the binary ** operator is implemented via the __pow__, __rpow__, and __ipow__ magic methods (the reality for np.ndarray is slightly more complicated since it's implemented in the C layer, but that's not actually important here). For Numpy arrays, these magic methods in turn appear to call numpy.power, so you can expect that ** will have the same behavior as documented for numpy.power. In particular,
Note that an integer type raised to a negative integer power will raise a ValueError.
With numpy you can just use numpy.power
arr = numpy.array([1,2,3])
print(numpy.power(3,arr)) # Outputs [ 3 9 27]
