Hi Olivier,
Sorry for the late reply - I have been on travel.
I have encountered the error in two separate cases; when I was using numpy
arrays, and when I was using numpy matrices.
In the case of a numpy array (Y), the operation is:
dot(Y,Y.conj().transpose())
and in the case of a matrix, wit
Hi Nathaniel,
The results of running memtest was a pass with no errors.
-Karl
Nathaniel Smith wrote:
>
> (You should still run memtest. It's very easy - just install it with your
> package manager, then reboot. Hold down the shift key while booting, and
> you'll get a boot menu. Choose memtest,
our
> package manager, then reboot. Hold down the shift key while booting, and
> you'll get a boot menu. Choose memtest, and then leave it to run
> overnight.)
>
> - Nathaniel
> On Dec 2, 2011 10:10 PM, "kneil" wrote:
>
>
--
View this message in context:
it on the other computer with same specs as this one.
If it runs without generating any NaN then I will proceed to a full memtest.
Thanks for the advice.
-Karl
On Thu, Dec 1, 2011 at 2:47 PM, kneil wrote:
Are you using non-ECC RAM, by chance? (Though if you have >4GB of ram, I
can't
with same specs as this one.
If it runs without generating any NaN then I will proceed to a full memtest.
Thanks for the advice.
-Karl
Joe Kington-2 wrote:
>
> On Thu, Dec 1, 2011 at 2:47 PM, kneil wrote:
>
>>
>> Hi Pierre,
>> I was thinking about uploading some exa
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..
Hi Oliver, indeed that was a typo, I should have used cut and paste. I was
using .transpose()
Olivier Delalleau-2 wrote:
>
> I guess it's just a typo on your part, but just to make sure, you are
> using
> .transpose(), not .transpose, correct?
>
> -=- Olivier
>
> 2011/11/30 Karl Kappler
>
