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Re: Hist_nd 3D +1 gridding / binning data [message #94257 is a reply to message #94253] Wed, 08 March 2017 13:09 Go to previous message
clement.feller@obspm. is currently offline  clement.feller@obspm.
Messages: 5
Registered: March 2017
Junior Member
Hi there Markus,

Thanks for your message, I'll try and see how much I can gain.
Actually, since monday, I found out why it'ld take so much time and resources: now the averaging task runs in about a minute or so.

The thing is, in practice my inputs consist of images and maps. So from 4 times 33 arrays of 2048x2048 pixels, I create my 4 aforementioned columns (data1, data2, data3, data4).
Then I selected an range of values corresponding to certain criterions (index).

In the end, I actually had written the lines for averaging task as follows:

for ijk=0L, .... do begin
newcol[ijk] = mean((data[index])[ri[init:stop]])
...
endfor

After performing the gridding and the actual binning, I wanted to be able to compare the original data and the gridded data, hence the way of writing things.
But of course, looping a command which loads a 160M table, queries a particular subset and averages up to 10M values from that subset tends to guzzle resources.

Anyways, it got me to look a bit more closely at things, and I've decided on another approach to my data to which this gridding will be more purposeful.
Once the analysis is done and the article is submitted, I'll post a link to it. :)

Cheers for the help,
/C
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