On Wed, Nov 25, 2015 at 12:21 AM, Sebastian Berg wrote:
> On Di, 2015-11-24 at 16:49 -0800, Eli Bendersky wrote:
> >
> >
> > On Mon, Nov 23, 2015 at 2:09 PM, Sebastian Berg
> > wrote:
> > On Mo, 2015-11-23 at 13:31 -0800, Eli Bendersky wrote:
> > > Hello,
> > >
> >
On Di, 2015-11-24 at 16:49 -0800, Eli Bendersky wrote:
>
>
> On Mon, Nov 23, 2015 at 2:09 PM, Sebastian Berg
> wrote:
> On Mo, 2015-11-23 at 13:31 -0800, Eli Bendersky wrote:
> > Hello,
> >
> >
> > I'm trying to understand the buffering done by the Numpy
>
On Mon, Nov 23, 2015 at 2:09 PM, Sebastian Berg
wrote:
> On Mo, 2015-11-23 at 13:31 -0800, Eli Bendersky wrote:
> > Hello,
> >
> >
> > I'm trying to understand the buffering done by the Numpy iterator
> > interface (the new post 1.6-one) when running ufuncs on arrays that
> > require broadcasting
On Mo, 2015-11-23 at 13:31 -0800, Eli Bendersky wrote:
> Hello,
>
>
> I'm trying to understand the buffering done by the Numpy iterator
> interface (the new post 1.6-one) when running ufuncs on arrays that
> require broadcasting. Consider this simple case:
>
> In [35]: m = np.arange(16).reshape(
Hello,
I'm trying to understand the buffering done by the Numpy iterator interface
(the new post 1.6-one) when running ufuncs on arrays that require
broadcasting. Consider this simple case:
In [35]: m = np.arange(16).reshape(4,4)
In [37]: n = np.arange(4)
In [39]: m + n
Out[39]:
array([[ 0, 2,