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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
>
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Christoph Gohle
- --
Max-Planck-Institut für Quantenoptik
Abteilung Quantenvielteilchensysteme
Hans-Kopfermann-Strasse 1
85748 Garching
[email protected]
tel: +49 89 32905 283
fax: +49 89 32905 313
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