Le samedi 22 janvier 2022, pawel.dar...@gmail.com a écrit :
> Hello,
>
> I am not sure that this is correct group for my problem but I hope
> someone can help me :)
>
> I try to analyze picture with porous material
> (https://python.neocast.eu/disc.png). I calculate a total quantity of
> each por
On Mon, Jan 24, 2022 at 2:15 AM Warren Weckesser
wrote:
> Thanks Sebastian for pointing out that the issue is (minor) page
> faults, and thanks Francesc for providing the links and the analysis
> of the situation. After reading those links and experimenting with
> malloc in a couple C programs,
On Mon, Jan 24, 2022 at 10:02 AM Francesc Alted wrote:
> Thanks for going down to the rabbit hole. It is now much clearer what's
> going on.
>
> All in all, hats off to Warren for this entertaining piece of
> investigation!
>
I can't resist. You'd expect someone called
https://en.wikipedia.or
On Mon, Jan 24, 2022 at 11:01 AM Francesc Alted wrote:
> On Mon, Jan 24, 2022 at 2:15 AM Warren Weckesser <
> warren.weckes...@gmail.com> wrote:
>
>> Thanks Sebastian for pointing out that the issue is (minor) page
>> faults, and thanks Francesc for providing the links and the analysis
>> of the
On Sun, 2022-01-23 at 14:12 -0800, Brock Mendel wrote:
> Have any of the numpy devs weighed in on this? If an efficient
> version of
> this were available in numpy there is a lot of pandas code I would
> enjoy
> ripping out.
As this is a Python float method, that is an argument for implementing
i
We have an interesting situation where a test suite that checks the value of
e^-inf is behaving differently depending on Numpy version. The minimal test
I'm using is:
#!/usr/bin/env python3
import numpy as np
np.seterr(under='raise')
print(np.exp(np.NINF))
With numpy version 1.19.5 and 1.20.3
On Mon, 2022-01-24 at 19:37 +, Michael Gutteridge wrote:
> We have an interesting situation where a test suite that checks the
> value of e^-inf is behaving differently depending on Numpy version.
> The minimal test I'm using is:
>
> #!/usr/bin/env python3
> import numpy as np
> np.seterr(und
