On 8/24/13, Tom Bennett wrote:
> Hi Warren,
>
> Yes you are absolutely right. I had some values close to log(x), where x is
> almost 0. That caused the problem.
>
> Thanks,
> Tom
Now the question is: why does `np.dot` mask the overflow warning?
In numpy 1.7.1, the default is that overflow shoul
Hi Warren,
Yes you are absolutely right. I had some values close to log(x), where x is
almost 0. That caused the problem.
Thanks,
Tom
On Sat, Aug 24, 2013 at 12:39 PM, Warren Weckesser <
warren.weckes...@gmail.com> wrote:
> On 8/24/13, Warren Weckesser wrote:
> > On 8/24/13, Tom Bennett wrot
On 8/24/13, Warren Weckesser wrote:
> On 8/24/13, Tom Bennett wrote:
>> Hi All,
>>
>> I have two arrays, A and B.A is 3 x 100,000 and B is 100,000. If I do
>> np.dot(A,B), I get [nan, nan, nan].
>>
>> However, np.any(np.isnan(A))==False and np.any(no.isnan(B))==False. And
>> also np.seterr(all='p
On 8/24/13, Tom Bennett wrote:
> Hi All,
>
> I have two arrays, A and B.A is 3 x 100,000 and B is 100,000. If I do
> np.dot(A,B), I get [nan, nan, nan].
>
> However, np.any(np.isnan(A))==False and np.any(no.isnan(B))==False. And
> also np.seterr(all='print') does not print anything.
>
> I am not w
Hi All,
I have two arrays, A and B.A is 3 x 100,000 and B is 100,000. If I do
np.dot(A,B), I get [nan, nan, nan].
However, np.any(np.isnan(A))==False and np.any(no.isnan(B))==False. And
also np.seterr(all='print') does not print anything.
I am not wondering what is going on and how to avoid.
In