I have a list of integers, e.g. i=[1,7,3,1,5]
which I first transform to a list of the respective binary representations of length L
, e.g. b=["001","111","011","001","101"]
with L=3
.
Now I want to compute at how many of the L
positions in the binary representation there is a 1
as well as a zero 0
. In my example the result would be return=2
since there is always a 1
in the third (last) position for these entries. I would be happy for any comment. I think, ideally I should do many Xor operations at the same time. However, I’m not sure how I can do this efficiently.
Edit: Thanks for the many answers!! I have to check which one is the fastest.
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Answer
One observation is that if you take the AND of all numbers, and also the OR of all numbers, then the XOR of those two results will have a 1 where the condition is fulfilled.
So:
from functools import reduce from operator import and_, or_ def count_mixed_bits(lst): xor = reduce(and_, lst) ^ reduce(or_, lst) return bin(xor).count("1") count_mixed_bits([1,7,3,1,5]) # 2