Thanks for all the answers, they were helpful!

I was using 1.7.0 and now installed from git:
https://github.com/numpy/numpy/archive/master.zip

And it looks like the memory leak is gone, so I guess I was hitting that
known memory leak bug. Thanks!

-Jaakko

On 02/26/2013 09:04 AM, Nathaniel Smith wrote:
> Is this with 1.7? There see a few memory leak fixes in 1.7, so if you
> aren't using that you should try it to be sure. And if you are using it,
> then there is one known memory leak bug in 1.7 that you might want to
> check whether you're hitting:
> https://github.com/numpy/numpy/issues/2969
> 
> -n
> 
> On 25 Feb 2013 13:41, "Jaakko Luttinen" <jaakko.lutti...@aalto.fi
> <mailto:jaakko.lutti...@aalto.fi>> wrote:
> 
>     Hi!
> 
>     I was wondering if anyone could help me in finding a memory leak problem
>     with NumPy. My project is quite massive and I haven't been able to
>     construct a simple example which would reproduce the problem..
> 
>     I have an iterative algorithm which should not increase the memory usage
>     as the iteration progresses. However, after the first iteration, 1GB of
>     memory is used and it steadily increases until at about 100-200
>     iterations 8GB is used and the program exits with MemoryError.
> 
>     I have a collection of objects which contain large arrays. In each
>     iteration, the objects are updated in turns by re-computing the arrays
>     they contain. The number of arrays and their sizes are constant (do not
>     change during the iteration). So the memory usage should not increase,
>     and I'm a bit confused, how can the program run out of memory if it can
>     easily compute at least a few iterations..
> 
>     I've tried to use Pympler, but I've understood that it doesn't show the
>     memory usage of NumPy arrays.. ?
> 
>     I also tried gc.set_debug(gc.DEBUG_UNCOLLECTABLE) and then printing
>     gc.garbage at each iteration, but that doesn't show anything.
> 
>     Does anyone have any ideas how to debug this kind of memory leak bug?
>     And how to find out whether the bug is in my code, NumPy or elsewhere?
> 
>     Thanks for any help!
>     Jaakko
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> 
> 
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