[Numpy-discussion] Initialization of array?

Daehyok Shin sdhyok at email.unc.edu
Wed Nov 29 18:37:54 CST 2000


Initialization on huge arrays is frequent operations in scientific
programming.
It must be efficient as much as possible.
So, I was surprisized to see the inner codes of ones() in Numpy.
It maybe use calloc() rather than malloc() in C level,
then for(..) for addition.
Why not use malloc() and for(...) simultaneously in C level
with a command such as:

a = arrray(1,shape=(10000,10000))

Daehyok Shin

----- Original Message -----
From: "Rob W. W. Hooft" <rob at hooft.net>
To: "Daehyok Shin" <sdhyok at email.unc.edu>
Cc: <numpy-discussion at lists.sourceforge.net>
Sent: Wednesday, November 29, 2000 1:00 PM
Subject: Re: [Numpy-discussion] Initialization of array?


> >>>>> "DS" == Daehyok Shin <sdhyok at email.unc.edu> writes:
>
>  DS> When I initialize an array, I use a = ones(shape)*initial_val
>
>  DS> But, I am wondering if Numpy has more efficient way. For example,
>  DS> a = array(initial_value, shape)
>
> Looking at the definition of "ones":
>
> def ones(shape, typecode='l', savespace=0):
>     """ones(shape, typecode=Int, savespace=0) returns an array of the
given
>     dimensions which is initialized to all ones.
>     """
>     return zeros(shape, typecode, savespace)+array(1, typecode)
>
> It looks like you could try a=zeros(shape)+initial_val instead.
>
> Hm.. I might do some experimenting.
>
> Rob
>
> --
> =====   rob at hooft.net          http://www.hooft.net/people/rob/  =====
> =====   R&D, Nonius BV, Delft  http://www.nonius.nl/             =====
> ===== PGPid 0xFA19277D ========================== Use Linux! =========
>




More information about the Numpy-discussion mailing list