On Wed, Nov 27, 2013 at 11:59:27AM +1100, Juan Nunez-Iglesias wrote:
> I'll also point out that np.copy has an "order" argument, so you can get back
> a
> Fortran-ordered array by doing
> >>> X_train = X_train.copy(order='F') # lets materialize the view
That's only in recentish versions of num
I'll also point out that np.copy has an "order" argument, so you can get
back a Fortran-ordered array by doing
>>> X_train = X_train.copy(order='F') # lets materialize the view
On Tue, Nov 26, 2013 at 11:53 PM, Peter Prettenhofer <
peter.prettenho...@gmail.com> wrote:
>
>
>
> 2013/11/26 Olivi
2013/11/26 Olivier Grisel
> 2013/11/26 Peter Prettenhofer :
> > Hi all,
> >
> > I'm currently modifying our tree code so that it runs on both fortran
> and c
> > continuous arrays. After some benchmarking I got aware of the following
> > numpy behavior that was contrary to what I was expecting::
On Tue, Nov 26, 2013 at 10:30 AM, Peter Prettenhofer <
peter.prettenho...@gmail.com> wrote:
>
> Hi all,
>
> I'm currently modifying our tree code so that it runs on both fortran and
c continuous arrays. After some benchmarking I got aware of the following
numpy behavior that was contrary to what I
2013/11/26 Peter Prettenhofer :
> Hi all,
>
> I'm currently modifying our tree code so that it runs on both fortran and c
> continuous arrays. After some benchmarking I got aware of the following
> numpy behavior that was contrary to what I was expecting::
>
> >>> X = # some feature matrix
> >>
