On Mon, Mar 25, 2024 at 5:54 PM Oscar Benjamin
wrote:
> On Sat, 9 Mar 2024 at 10:16, Ralf Gommers wrote:
> >
> > On Sat, Mar 9, 2024 at 2:03 AM Oscar Benjamin <
> oscar.j.benja...@gmail.com> wrote:
> >>
> >> On Sat, 9 Mar 2024 at 00:44, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
> >>
On Sat, 9 Mar 2024 at 10:16, Ralf Gommers wrote:
>
> On Sat, Mar 9, 2024 at 2:03 AM Oscar Benjamin
> wrote:
>>
>> On Sat, 9 Mar 2024 at 00:44, Charles R Harris
>> wrote:
>> >
>> > About a month from now.
>>
>> What will happen about a month from now? It might seem obvious to you
>> but I can i
On Mon, 25 Mar 2024 at 20:09, Charles R Harris
wrote:
>
>
> On Mon, Mar 25, 2024 at 11:28 AM Luca Bertolotti <
> luca72.bertolo...@gmail.com> wrote:
>
>> Hello
>> in a vb program they use 3rd degree approx and get this value including
>> displacement:(SC)
>> [image: image.png]
>>
>> Ii think that
On Mon, Mar 25, 2024 at 11:28 AM Luca Bertolotti <
luca72.bertolo...@gmail.com> wrote:
> Hello
> in a vb program they use 3rd degree approx and get this value including
> displacement:(SC)
> [image: image.png]
>
> Ii think that i'm doing the same with numpy but I get different value does
> anyone
Hello Luca,
I am a bit confused by the output of VB script.
Equation is: y = f(x), where
x is in the order of 0-2K
y is in the order of 5-10K
The output of fitted polynomial is in y-space, thus I would expect fitted
values to be similar to those of Y.
Now, sc values are very small and alternat
Hello
in a vb program they use 3rd degree approx and get this value including
displacement:(SC)
[image: image.png]
Ii think that i'm doing the same with numpy but I get different value does
anyone can help me please
radious = [1821, 1284, 957, 603,450, 245]
y = [6722, 6940, 7227, 7864,8472, 10458
On Mon, Mar 25, 2024 at 2:24 PM Matěj Cepl wrote:
> Hello,
>
> As a maintainer of Python packages for openSUSE/SUSE,
> I would like to ask for help with our bug
> https://bugzilla.suse.com/1221902. It seems to us that the latest
> version of NumPy suddenly requires z15 CPU generation, although
>
On Mon, 2024-03-25 at 13:49 +, percynichols...@gmail.com wrote:
> Many thanks!
>
> Just one more inquiry along those lines, if I may. The code asserts
> that clip should outpace np.maximum(mp.minumum(arr, max), min).
> Despite this:
> *time a = np.arange(100)it.clip(4, 20) # 8.48 µs
> %time
Many thanks!
Just one more inquiry along those lines, if I may. The code asserts that clip
should outpace np.maximum(mp.minumum(arr, max), min). Despite this:
*time a = np.arange(100)it.clip(4, 20)# 8.48 µs
%timeit np.maximum(np.minimum(a, 20), 4)2.09 nanoseconds
Will this be the norm?
__
Hello,
As a maintainer of Python packages for openSUSE/SUSE,
I would like to ask for help with our bug
https://bugzilla.suse.com/1221902. It seems to us that the latest
version of NumPy suddenly requires z15 CPU generation, although
it used to be OK with z13+ before, and unfortunately that is the
10 matches
Mail list logo
