[Numpy-discussion] Numpy array slicing
Olivier Delalleau
shish@keba...
Thu Feb 9 05:55:18 CST 2012
This was actually discussed very recently (for more details:
http://mail.scipy.org/pipermail/numpy-discussion/2012-February/060232.html).
It's caused by mixing slicing with advanced indexing. The resulting shape
is the concatenation of a first part obtained by broadcasting of the
non-slice items (in your case, 0 and mask[0] being broadcasted to shape
(12285,), the number of non-zero elements in mask[0]), followed by a second
part obtained by the slice items (in your case extracting dimensions #1 and
#3 of a, i.e. shape (4, 2)).
So the final shape is (12285, 4, 2).
-=- Olivier
Le 9 février 2012 06:32, Eirik Gjerløw <eirik.gjerlow@astro.uio.no> a écrit
:
> Hello,
>
> (also sent to Scipy-User, sorry for duplicates).
>
> This is (I think) a rather basic question about numpy slicing. I have
> the following code:
>
> In [29]: a.shape
> Out[29]: (3, 4, 12288, 2)
>
> In [30]: mask.shape
> Out[30]: (3, 12288)
>
> In [31]: mask.dtype
> Out[31]: dtype('bool')
>
> In [32]: sum(mask[0])
> Out[32]: 12285
>
> In [33]: a[[0] + [slice(None)] + [mask[0]] + [slice(None)]].shape
> Out[33]: (12285, 4, 2)
>
> My question is: Why is not the final shape (4, 12285, 2) instead of
> (12285, 4, 2)?
>
> Eirik Gjerløw
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