# [Numpy-discussion] Does x[True] trigger basic or advanced indexing?

Eric Wieser wieser.eric+numpy at gmail.com
Thu Dec 14 11:24:09 EST 2017

```It sounds like you're using an old version of numpy, where boolean scalars
were interpreted as integers.

What version are you using?

Eric

On Thu, Dec 14, 2017, 04:27 Joe <solarjoe at posteo.org> wrote:

> Hello,
> thanks for you feedback.
>
> Sorry, if thie question is stupid and the case below does not make
> sense.
> I am just trying to understand the logic.
> For
>
> x = np.random.rand(2,3)
>
> x[True]
> x[(True,)]
>
> or
>
> x[False]
> x[(False,)]
>
> where True and False are not arrays,
> it will pick the first or second row.
>
> Is this basic indexing then with one the rules
> - obj is an integer
> - obj is a tuple of slice objects and integers.
> ?
>
>
> Am 13.12.2017 21:49 schrieb Eric Wieser:
> > Increasingly, NumPy does not considers booleans to be integer types,
> > and indexing is one of these cases.
> >
> > So no, it will not be treated as a tuple of integers, but as a 0d mask
> >
> > Eric
> >
> > On Wed, 13 Dec 2017 at 12:44 Joe <solarjoe at posteo.org> wrote:
> >
> >> Hi,
> >>
> >> yet another question.
> >>
> >> I looked through the indexing rules in the
> >> documentation but I count not find which one
> >> applies to x[True] and x[False]
> >>
> >> that might e.g result from
> >>
> >> import numpy as np
> >> x = np.array(3)
> >> x[x>5]
> >> x[x<1]
> >> x[True]
> >> x[False]
> >>
> >> x = np.random.rand(2,3)
> >> x[x>5]
> >> x[x<1]
> >> x[True]
> >> x[False]
> >>
> >> I understood that they are equivalent to
> >>
> >> x[(False,)]
> >>
> >> I tested it and it looks like advanced indexing,
> >> but I try to unterstand the logic behind this,
> >> if there is any :)
> >>
> >> In x[x<1] the x<1 is a mask and thus I guess it is a
> >> "tuple with at least one sequence object or ndarray (of data type
> >> integer or bool)", right?
> >>
> >> Or will x[True] trigger basic indexing as it is "a tuple of
> >> integers"
> >> because True will be converted to Int?
> >>
> >> Cheers,
> >> Joe
> >> _______________________________________________
> >> NumPy-Discussion mailing list
> >> NumPy-Discussion at python.org
> >> https://mail.python.org/mailman/listinfo/numpy-discussion [1]
> >
> >
> > ------
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> >
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