The distinction that boolean indexing has over the other 2 methods of indexing is that it can guarantee that it references a position at most once. Slicing and scalar indexes are also this way, hence why these methods allow for in-place assignments. I don't see boolean indexing as an extension of orthogonal indexing because of that.
Ben Root On Thu, Apr 2, 2015 at 2:41 PM, Stephan Hoyer <sho...@gmail.com> wrote: > On Thu, Apr 2, 2015 at 11:03 AM, Eric Firing <efir...@hawaii.edu> wrote: > >> Fancy indexing is a horrible design mistake--a case of cleverness run >> amok. As you can read in the Numpy documentation, it is hard to >> explain, hard to understand, hard to remember. > > > Well put! > > I also failed to correct predict your example. > > >> So I think you should turn the question around and ask, "What is the >> actual real-world use case for fancy indexing?" How often does real >> code rely on it? > > > I'll just note that Indexing with a boolean array with the same shape as > the array (e.g., x[x < 0] when x has greater than 1 dimension) technically > falls outside a strict interpretation of orthogonal indexing. But there's > not any ambiguity in adding that as an extension to orthogonal indexing > (which otherwise does not allow ndim > 1), so I think your point still > stands. > > Stephan > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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