Re: [Numpy-discussion] Initialization of array?

[Daehyok S. <sd...@em...>]

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" <ro...@ho...>
To: "Daehyok Shin" <sd...@em...>
Cc: <num...@li...>
Sent: Wednesday, November 29, 2000 1:00 PM
Subject: Re: [Numpy-discussion] Initialization of array?


> >>>>> "DS" == Daehyok Shin <sd...@em...> 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
>
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