anks again!
MJ
-Original Message-
From: numpy-discussion-boun...@scipy.org
[mailto:numpy-discussion-boun...@scipy.org] On Behalf Of Christopher Barker
Sent: Thursday, April 30, 2009 12:16 PM
To: Discussion of Numerical Python
Subject: Re: [Numpy-discussion] Timing array construction
Ma
age-
> From: numpy-discussion-boun...@scipy.org
> [mailto:numpy-discussion-boun...@scipy.org] On Behalf Of Eric Firing
> Sent: Wednesday, April 29, 2009 11:49 PM
> To: Discussion of Numerical Python
> Subject: Re: [Numpy-discussion] Timing array construction
>
> Mark Janikas wro
Mark Janikas wrote:
> I have a lot of array constructions in my code that use
> NUM.array([list of values])... I am going to replace it with the
> empty allocation and insertion.
It may not be worth it, depending on where list_of_values comes from/is.
A rule of thumb may be: it's going to be slow
ring
Sent: Wednesday, April 29, 2009 11:49 PM
To: Discussion of Numerical Python
Subject: Re: [Numpy-discussion] Timing array construction
Mark Janikas wrote:
> Hello All,
>
>
>
> I was exploring some different ways to concatenate arrays, and using
> "c_" is the fa
Mark Janikas wrote:
> Hello All,
>
>
>
> I was exploring some different ways to concatenate arrays, and using
> “c_” is the fastest by far. Is there a difference I am missing that can
> account for the huge disparity? Obviously the “zip” function makes the
> “as array” and “array” calls sl
Hello All,
I was exploring some different ways to concatenate arrays, and using "c_" is
the fastest by far. Is there a difference I am missing that can account for
the huge disparity? Obviously the "zip" function makes the "as array" and
"array" calls slower, but the same arguments (xCoords,
