On Tue, Oct 17, 2006 at 10:01:51AM -0600, Travis Oliphant wrote:
> Charles R Harris wrote:
>
> > Travis,
> >
> > I note that
> >
> > >>> a = arange(6).reshape(2,3,order='F')
> > >>> a
> > array([[0, 1, 2],
> > [3, 4, 5]])
> >
> > Shouldn't that be 3x2? Or maybe [[0,2,4],[1,3,5]]? Reshape is making a
> > copy, but flat, flatten, and tostring all show the elements in 'C'
> > order. I ask because I wonder if changing the order can be used to
> > prepare arrays for input into the LaPack routines.
>
>
> The order argument to reshape means (how should the big-chunk of data be
> interpreted when you reshape). So, yes, this should be
> [[0,2,4],[1,3,5]]. It is a bug that it does not do the right thing in
> this case.
A bit counter-ituitive (I somehow expect reshape to return an array
that satisfies all the constraints specified as parameters -- i.e.
shape and order in memory), but consistent with Numeric.
What confuses me is that, if you call the array constructor, you get
In [2]: N.array(N.array([[1,2,3],[4,5,6]]),order='F')
Out[2]:
array([[1, 2, 3],
[4, 5, 6]])
so here 'order' means something else.
So then you do
x = N.array([[0,1,2],[3,4,5]],order='F')
x.reshape((2,3),order='C')
and you get
array([[0, 1, 2],
[3, 4, 5]])
Hmm.
Cheers
Stéfan
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