> >
http://mail.scipy.org/mailman/listinfo/numpy-discussion
> >
>
> Hi,
> I can get this with 64-bit Win 7, 32-bit Python 2.6, 2.7
(below) and
> 3.1 and numpy 1.6b (fresh install) IDLE and the command line.
I can
> also confirm the 'ValueError' with Python2.6 and numpy 1.51 on the
> same system.
>
> Actually this is 'weird' when printing and crashed with the
range -
> accessing unassigned memory?
> A smaller array gives an numpy error or memory error in idle.
>
> Bruce
>
>
> > >> import numpy as np
> > >> x=np.zeros((262144, 262144))
> > >> x
> array([], shape=(262144, 262144), dtype=float64)
> > >> x[0,0]
> 2.1453735050108555e-314
> > >> x[1:10,1:10]
>
> > >> ================================ RESTART
> ================================
> > >> import numpy as np
>
> > >> x=np.zeros((26214, 26214))
>
> Traceback (most recent call last):
> File "<pyshell#7>", line 1, in <module>
> x=np.zeros((26214, 26214))
> ValueError: array is too big.
> > >>
> > >> x=np.zeros((262144, 26214))
>
> Traceback (most recent call last):
> File "<pyshell#8>", line 1, in <module>
> x=np.zeros((262144, 26214))
> MemoryError
> _____
>
>
> This was fixed before, maybe it got broken again. Since this looks
> windows specific, I'm guessing it has something to do with the size of
> long being 32 bits.
>
> The previous problem was integer overflow when multiplying the
> dimensions together to get the array size when repeated divisions
of the
> maximum size should have be used instead.
>
> Chuck
Could be related to this change:
<
https://github.com/numpy/numpy/commit/fcc6cc73ddcb1fc85446ba9256ac24ecdda6c6d8#L1L1121>
My, that does look suspicious ;) Could you revert that loop and test it out?
There was also a function for doing that check, I don't recall which,
and it should probably be checked to make sure it remains as was.
Chuck