On Thu, 2017-12-14 at 16:24 +0000, Eric Wieser wrote: > It sounds like you're using an old version of numpy, where boolean > scalars were interpreted as integers. > What version are you using? > Eric >
Indeed, you are maybe using a pre 1.9 version (post 1.9 should at least have a DeprecationWarning or some such, though you might not notice it IIRC). For newer versions you should get boolean indexing, the result of it may be a bit confusing. It is advanced indexing, basically with False giving you an empty array (with an extra dimension of size 0) and True being much like an `np.newaxis`. It all makes perfect sense if you think of it of a 0-d array picking.... The same thing is true for example for lists of booleans. - Sebastian > On Thu, Dec 14, 2017, 04:27 Joe <solar...@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 <solar...@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@python.org > > >> https://mail.python.org/mailman/listinfo/numpy-discussion [1] > > > > > > > > > Links: > > > ------ > > > [1] https://mail.python.org/mailman/listinfo/numpy-discussion > > > > > > _______________________________________________ > > > NumPy-Discussion mailing list > > > NumPy-Discussion@python.org > > > https://mail.python.org/mailman/listinfo/numpy-discussion > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion
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