Yes, clearing is not the proper word but the "trick" works only work for 0
(I'll get the same result in both cases).
Nicolas
> On 27 Dec 2016, at 20:52, Chris Barker wrote:
>
> On Mon, Dec 26, 2016 at 1:34 AM, Nicolas P. Rougier
> wrote:
>
> I'm trying to understand why viewing an array
On Mon, Dec 26, 2016 at 1:34 AM, Nicolas P. Rougier <
nicolas.roug...@inria.fr> wrote:
>
> I'm trying to understand why viewing an array as bytes before clearing
> makes the whole operation faster.
> I imagine there is some kind of special treatment for byte arrays but I've
> no clue.
>
I notice
Might be os-specific, too. Some virtual memory management systems might
special case the zeroing out of memory. Try doing the same thing with a
different value than zero.
On Dec 26, 2016 6:15 AM, "Nicolas P. Rougier"
wrote:
Thanks for the explanation Sebastian, makes sense.
Nicolas
> On 26 D
Thanks for the explanation Sebastian, makes sense.
Nicolas
> On 26 Dec 2016, at 11:48, Sebastian Berg wrote:
>
> On Mo, 2016-12-26 at 10:34 +0100, Nicolas P. Rougier wrote:
>> Hi all,
>>
>>
>> I'm trying to understand why viewing an array as bytes before
>> clearing makes the whole operatio
On Mo, 2016-12-26 at 10:34 +0100, Nicolas P. Rougier wrote:
> Hi all,
>
>
> I'm trying to understand why viewing an array as bytes before
> clearing makes the whole operation faster.
> I imagine there is some kind of special treatment for byte arrays but
> I've no clue.
>
Sure, if its a 1-byte
Hi all,
I'm trying to understand why viewing an array as bytes before clearing makes
the whole operation faster.
I imagine there is some kind of special treatment for byte arrays but I've no
clue.
# Native float
Z_float = np.ones(100, float)
Z_int = np.ones(100, int)
%timeit Z_fl
