On 7/10/07, Mark.Miller <[EMAIL PROTECTED]> wrote:
Just ran across something that doesn't quite make sense to me at the
moment.
Here's some code:
>>> numpy.__version__
'1.0.2'
>>>
>>> def f1(b,c):
b=b.astype(int)
c=c.astype(int)
return b,c
>>> b,c = numpy.fromfunction(f1,(5,5))
>>> a=numpy.zeros((2,12,5,5),int)
>>> a1=a[0]
>>> a1[:,b,c].shape
(12, 5, 5)
>>> a[0,:,b,c].shape
(5, 5, 12) ###why does this not return (12,5,5)?
>>>
So in a nutshell, it's not completely clear to me why these are
returning arrays of different shapes. Can someone shed some light?
It's because you are using arrays as indices (aka Fancy-Indexing). When you
do this everything works differently. In this case, everything is being
broadcast to the same shape. As I understand it (and I try to use only the
simplest forms of fancy indexing), what you are doing is equivalent to:
--
. __
. |-\
.
. [EMAIL PROTECTED]
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