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Re: IDL, arrays, and memory [message #33898 is a reply to message #33896] Tue, 04 February 2003 09:23 Go to previous messageGo to previous message
JD Smith is currently offline  JD Smith
Messages: 850
Registered: December 1999
Senior Member
On Tue, 04 Feb 2003 09:54:15 -0700, David Fanning wrote:

> Sean Raffuse (sean@me.wustl.edu) writes:
>
>> I would like to create a jagged array. My array is something like:
>>
>> array = intarr(3600, 1600, 240 or less)
>>
>> Do I save space by creating a jagged array where the 3rd dimension is
>> of variable size? Is that even possible? Should I just stick with
>> 3600x1600x240?
>
> What language are you thinking of doing this in, Sean? :-)
>
> As a general rule, it is better to get all the memory you need at once,
> then trim. This avoids memory fragmentation problems, etc.
>
> But "jagged arrays". I'd like to see this when you are finished. :-)
>

I think Sean probably means "ragged" array, which, in C, is
essentially an array of pointers to variable-length arrays, often
allocated dynamically at run time. It's a standard memory-saving
technique. In fact, when you create a simple static array of strings,
ala:

char *msg[3]={"Eat", "My", "Grits"};

you are implicitly creating a ragged array.

You can easily create such a beast in IDL:

array=ptrarr(3600,1600)

for i=0,n_elements(array)-1 do array[i]=ptr_new(vector_less_than_240)

However, whereas in C the difference in terms of speed and algorithm
design is negligible between using a ragged array and a "wasteful"
full 3D array, this is not true in IDL. In particular, you can't use
most of IDL's fast array-based operators with an array of pointers;
you're stuck accessing each element in a loop, which will be markedly
slower for a data structure of this size.

You must balance the memory saved against the speed and flexibility
with which you can operate on the data. This is a common theme in
IDL, which, in many instances, trades increased memory usage for
greater speed of execution. Often you can find other ways to organize
the data which reduces the memory footprint while preserving much of
the same flexibility had by putting it all in a single array. Or you
can use, e.g., NaN values to fill the "wasted" array elements and
avoid having to treat them specially.

Good luck,

JD
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