# [Numpy-discussion] numpy dot returns [nan nan nan]

Warren Weckesser warren.weckesser@gmail....
Sat Aug 24 12:39:53 CDT 2013

```On 8/24/13, Warren Weckesser <warren.weckesser@gmail.com> wrote:
> On 8/24/13, Tom Bennett <tom.bennett@mail.zyzhu.net> 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 wondering what is going on and how to avoid.
>>
>> In case it is important, A and B are from the normal equation of doing
>> regression. I am regressing 100,000 observations on 3 100,000 long
>> factors.
>>
>> Thanks,
>> Tom
>>
>
> What are the data types of the arrays, and what are the typical sizes
> of the values in these arrays?  I can get all nans from np.dot if the
> values are huge floating point values:
>
> ```
> In [79]: x = 1e160*np.random.randn(3, 10)
>
> In [80]: y = 1e160*np.random.randn(10)
>
> In [81]: np.dot(x, y)
> Out[81]: array([ nan,  nan,  nan])
> ```

...and that happens because some intermediate terms overflow to inf or
-inf, and adding these gives nan:

```
In [89]: x = np.array([1e300])

In [90]: y = np.array([1e10])

In [91]: np.dot(x,y)
Out[91]: inf

In [92]: x2 = np.array([1e300, 1e300])

In [93]: y2 = np.array([1e10,-1e10])

In [94]: np.dot(x2, y2)
Out[94]: nan
```

Warren

>
> Warren
>
```