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.
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