[Numpy-discussion] Fancy indexing with masks

Robert Kern robert.kern@gmail....
Tue Sep 20 02:43:52 CDT 2011


2011/9/20 Stéfan van der Walt <stefan@sun.ac.za>:
> Hi all,
>
> Matthew Brett showed me an interesting code snippet this evening:
>
> # Construct input data
>
> In [15]: x
> Out[15]:
> array([[ 0,  1,  2],
>       [ 3,  4,  5],
>       [ 6,  7,  8],
>       [ 9, 10, 11]])
>
> # Fancy indexing with 1D boolean array
>
> In [16]: x[np.array([True, False, True])]
> Out[16]:
> array([[0, 1, 2],
>       [6, 7, 8]])
>
> # Fancy indexing with 2D boolean array
>
> In [17]: x[np.array([[True, False, True]])]
> Out[18]: array([0, 2])
>
>
> I guess it's been a long day, but why does this work at all?
>
> I expected the first example to break, because the 1D mask does not
> match the number of rows in x.  In the second example, I expected an
> error because the 2D mask was not of the same shape as x.  But, oddly,
> both work. There's also no attempt at broadcasting indexes.

If the array is short in a dimension, it gets implicitly continued
with Falses. You can see this in one dimension:

[~]
|1> x = np.arange(12)

[~]
|2> x[np.array([True, False, True])]
array([0, 2])


I honestly don't know if this is documented or tested anywhere or even
if this existed in older versions.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco


More information about the NumPy-Discussion mailing list