On Thu, Dec 1, 2011 at 2:47 PM, kneil <magnetotellur...@gmail.com> wrote:
>
> Hi Pierre,
> I was thinking about uploading some examples but strangely, when I store
> the
> array using for example: np.save('Y',Y)
> and then reload it in a new workspace, I find that the problem does not
> reproduce. It would seem somehow to be
> associated with the 'overhead' of the workspace I am in...
>
> The context here is that I read in 24 files, totaling about 7GB, and then
> forming data matrices of size 24 x N, where N varies. I tried for example
> this morning to run the same code, but working with only 12 of the files -
> just to see if NaNs appeared. No NaN appeared however when the machine was
> being less 'taxed'.
>
Are you using non-ECC RAM, by chance? (Though if you have >4GB of ram, I
can't imagine that you wouldn't be using ECC...)
Alternately, have you run memtest lately? That sound suspiciously like bad
ram...
>
> Strangely enough, I also seterr(all='raise') in the workspace before
> executing this (in the case where I read all 24 files and do net NaN) and I
> do not get any messages about the NaN while the calculation is taking
> place.
>
> If you want to play with this I would be willing to put the data on a file
> sharing site (its around 7.1G of data) together with the code and you could
> play with it from there. The code is not too many lines - under 100 lines,
> and I am sure I could trim it down from there.
>
> Let me know if you are interested.
> cheers,
> K
>
>
> Pierre Haessig-2 wrote:
> >
> > Le 01/12/2011 02:44, Karl Kappler a écrit :
> >> Also note that I have had a similar problem with much smaller arrays,
> >> say 24 x 3076
> > Hi Karl,
> > Could you post a self-contained code with such a "small" array (or even
> > smaller. the smaller, the better...) so that we can run it and play with
> > it ?
> > --
> > Pierre
> >
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> >
> >
>
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