On 7/10/07, Mark.Miller <mpmusu@cc.usu.edu> 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: