Combining boolean masks, why is in Python: [False, True] and [True, False] == [True, False]

Question

I was busy with combining masks and it strikes me that:

>>> [False, True] and [True, False]
[True, False]

and

>>> [True, False] and [False, True]
[False, True]

Why is this the case? Why shouldn't I expect it to be [False, False] in both cases?

I also think this is why np.logical_and() exists in Numpy:

>> np.logical_and([True, False], [False, False])
array([False, False])

You are not comparing what you think you are comparing. `bool([False, True])` is `True` and `bool([True, False])` is also `True`. — tripleee, Jul 30 '20 at 10:44

Sayandip Dutta · Accepted Answer · 2020-07-30T10:50:43.983

This is the same reason why:

>>> (1,2) and (3,4)
(3, 4)

You need to understand that this is not doing element-wise comparison as opposed to np.logical_and.

The way and works is, if you have a and b, it checks whether a is False, if yes, return a else return b, does not matter what the value of b is.

In your case [False, True] is not False:

>>> bool([False, True])
True

Because it is a non-empty list, even [False, False] is True. So in the case of [False, True] and [True, False], it checks to see whether [False, True] is False, which it is not, so it returns the second value. Same for the other case.

A python implementation of the and or logic would be:

def AND(first, second):
    if bool(first) == True:
        return second
    else:
        return first


def OR(first, second):
    if bool(first) == True:
        return first
    else:
        return second

Combining boolean masks, why is in Python: [False, True] and [True, False] == [True, False]

1 Answers1