On 9/13/06, Francesc Altet [EMAIL PROTECTED] wrote:
Well, it seems that malloc actually takes more time when asking for more
space. However, this can't be the reason why Pierre is seeing that:
a = numpy.exp(a) [1]
is slower than
numpy.exp(a,out=a) [2]
as I'd say that this increment in
Hi,
one word in advance, instead of optimizing it is advisable to seek for a way
to refactorize the algorithm using smaller arrays, since this kind of
optimization almost certainly reduces readability. If you do it, comment
well. ;-)
If you have very large arrays and want to do some
Hi,
I would like to have information on the best techniques to do in-place
calculations and to minimize temporary array creations. To me this
seems to be very important whenever the arrays become very large.
I already know about the ufunc in-place functionality (which is great).
More
Hello again,
On 9/12/06, Francesc Altet [EMAIL PROTECTED] wrote:
Hello Pierre,
[...]
Well, in some way, there is a temporary array creation that is
immediately bound to B, so in the end, the temporary is not so
temporary, but a new (bounded) object. Obviously, the object that was
El dt 12 de 09 del 2006 a les 13:17 -0400, en/na Pierre Thibault va
escriure:
Hello again,
On 9/12/06, Francesc Altet [EMAIL PROTECTED] wrote:
Hello Pierre,
[...]
Well, in some way, there is a temporary array creation that is
immediately bound to B, so in the end, the temporary is
