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Hi
Am 08.03.2012 um 20:39 schrieb Pauli Virtanen:

> 08.03.2012 17:37, Christoph Gohle kirjoitti:
>> thanks for testing. I have now tried on different platforms. I get
>> all kinds of crashes on os x (now with numpy 1.6.1) and windows
>> with numpy 1.6.0. On Ubuntu with numpy 1.3.0 I get a hughe memory
>> leak...
>> 
>> Any hints would be welcome.
> 
> The type object inherits `tp_alloc` from Numpy. This routine always
> allocates memory of size NPY_SIZEOF_PYARRAYOBJECT for the
> PyArrayObject. Therefore, the write to new->unit in your
> __array_finalize__ goes to unallocated memory.
> 
> This is probably a bug in Numpy --- arrayobject.c:array_alloc should
> respect the size specified by the subtype.
> 
> A workaround is probably to specify a suitable tp_alloc routine yourself:
> 
>   PyType_GenericAlloc,        /* tp_alloc */
>    unitArray_new,              /* tp_new */
>    _PyObject_Del               /* tp_free */
> 
OK, I did that. And I get no more segfaults as far as I can tell. But there is 
still a memory leak:

In [1]: import spampub

In [2]: a=[spampub.UnitArray(i,{'s':i}) for i in xrange(100000)]

In [3]: del a

after the last two statements, python uses ~60MB more memory than before.

Thanks for your help
Christoph
> -- 
> Pauli Virtanen
> 
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion


Christoph Gohle
- --
Max-Planck-Institut für Quantenoptik
Abteilung Quantenvielteilchensysteme
Hans-Kopfermann-Strasse 1
85748 Garching

christoph.go...@mpq.mpg.de
tel: +49 89 32905 283
fax: +49 89 32905 313



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