Hi!
2017-11-26 4:31 GMT+03:00 Juan Nunez-Iglesias :
>
> On 26 Nov 2017, 12:27 PM +1100, Nathaniel Smith , wrote:
>
> It turns out that the PEP 484 type system is *mostly* not useful for
> this. They're really designed for checking consistency across a large
>
Hi,
I was trying to sort an array (N, 3) by rows, and firstly come with this
solution:
N = 100
arr = np.random.randint(-100, 100, size=(N, 3))
dt = np.dtype([('x', int),('y', int),('z', int)])
*arr.view(dtype=dt).sort(axis=0)*
Then I found another way using lexsort function
*:*
*idx =
h is 1D. 1D arrays do not have an axis=1. You actually
> want to iterate over the columns, so np.lexsort(a.T) is the correct
> phrasing of that. No idea about the speed difference.
>
>-Joe
>
> On Fri, Oct 20, 2017 at 6:00 AM, Kirill Balunov <kirillbalu...@gmail.com>
>
Only concerns #4 from Ilhan's list.
ср, 26 июн. 2019 г. в 00:01, Ralf Gommers :
>
> []
>
> Perhaps not full consensus between the many people with different opinions
> and interests. But for the first one, arr.T change: it's clear that this
> won't happen.
>
To begin with, I must admit