[SciPy-Dev] Fwd: Re: GSoC 2017: BSpline support

Aman Pratik amanpratik10 at gmail.com
Sat Mar 25 03:23:47 EDT 2017


This seems like a nice option, though I am not sure of its importance for
computing derivatives. I mean you can use any one of the provided methods
to compute the derivative. Please correct me if I am missing something.




On 25 March 2017 at 11:53, Xavier Barthelemy <xabart at gmail.com> wrote:

> Dear everyone,
>
> While we are talking about splining, I would like to add a request if
> possible.
> I am a heavy user of the splprep and co routines, and many times I need to
> get the local polynomial coefficients to compute the derivatives, and found
> the analitical zeros.
> I had found a recipe on stackoverlord years ago, on how to get back to
> local coefficient from the spline description.
>
>
> Maybe a method, or an option, returning the local polynomial coefficients
> (and the interval?) could be implemented?
> it's my 2 cents as a user
>
> thanks for considering it and please, discard if you think it's not fit.
>
> All the best
> Xavier
>
> 2017-03-25 15:29 GMT+11:00 Aman Pratik <amanpratik10 at gmail.com>:
>
>> Seems interesting. Though adding this would require doing away with some
>> of the other part(s) of the project. I will do some research on it.
>> Meanwhile, lets wait for feedback from the mentors.
>>
>>
>>
>>
>> On 25 March 2017 at 04:43, Stefan van der Walt <stefanv at berkeley.edu>
>> wrote:
>>
>>> On Fri, Mar 24, 2017, at 12:19, Aman Pratik wrote:
>>>
>>> Hello,
>>> This is my second Draft, Proposal : Second Draft
>>> <https://github.com/amanp10/scipy/wiki/GSoC-2017-:-Improve-support-for-B-splines>
>>>
>>>
>>> Would this be a good opportunity to add subdivision splines to SciPy?
>>> Their implementation (at least in 1D) is simple, and they give good
>>> locality around nodes (i.e., yield predictable curves, useful for spline
>>> design).
>>>
>>> An example is given here:
>>>
>>> https://gist.github.com/stefanv/a28d61694fe8f3ef2325b23cbc51312a
>>>
>>> Stéfan
>>>
>>>
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>>>
>>
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>
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