hello
i'm not sire of what they do and I don't have the source I see just that
they wrote y= f(x) 3rd order
[image: image.png]

using p = cheb.Chebyshev.fit(x, y, 3 , window=[.......])
I see that if I change the upper value of the window I can reach similar
solution but I don't understand the criteria of changing.
Any help is very appreciated
Regards
Luca

Il giorno lun 25 mar 2024 alle ore 20:43 Andrea Gavana <
andrea.gav...@gmail.com> ha scritto:

> On Mon, 25 Mar 2024 at 20:09, Charles R Harris <charlesr.har...@gmail.com>
> 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 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]
>>> p = np.polyfit(radious, y, 3,)
>>> t = np.polyval(p, radious)
>>> [ 6703.33694696  7061.23784145  7051.49974149  7838.84623289
>>>   8654.47847319 10373.60076402]
>>> You can see polyval is difference from the sc. of the table
>>> Any help is really appreciated
>>>
>>
>> What is sc?
>>
>
>
> At the beginning I thought it was the difference between the fitted y and
> the measured y, but of course that is not the case.
>
> For what is worth, doing it in Excel using LINEST:
>
> *=LINEST(A2:A7, B2:B7^{1,2,3})*
>
> And then back-calculating the results of the fit I get this for the
> "fitted" y:
>
> 6703.34, 7061.24, 7051.50, 7838.85, 8654.48, 10373.60
>
> Which are indeed the same numbers obtained by numpy polyfit. Also get the
> same if you use the automatic line fitting in an Excel graph.
>
> Not that I trust Excel with anything, it was just for fun.
>
> Not entirely clear what the OP is doing with VB, but either we are missing
> a crucial piece of information or the VB code is incorrect.
>
> Andrea.
>
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