Maybe this addresses Robert's needs: http://www.scholarpedia.org/article/Finite_difference_method#FD_formulas_in_... https://github.com/pbrod/numdifftools/blob/master/numdifftools/fornberg.py Per A. -----Original Message----- From: SciPy-Dev [mailto:scipy-dev-bounces@scipy.org] On Behalf Of Jonathan Stickel Sent: 10. november 2016 18:32 To: scipy-dev@scipy.org Subject: Re: [SciPy-Dev] Differentiate function On 11/10/16 01:19 , Thomas Haslwanter wrote:
The current discussion lacks a reference to the existing Savitzky-Golay filter https://scipy.github.io/devdocs/generated/scipy.signal.savgol_filter.h tml which - to my understanding - should solves most of Robert's problems.
thomas
No, I don't think this addresses Robert's needs. That is simply a data smoother (and arguably inferior to other data-smoothing methods). Although it does have an option to provide a derivative, it presumes the data are equally spaced.
On Thu, Nov 10, 2016 at 8:10 AM, Ralf Gommers <ralf.gommers@gmail.com <mailto:ralf.gommers@gmail.com>> wrote:
On Wed, Nov 9, 2016 at 8:01 AM, Pauli Virtanen <pav@iki.fi <mailto:pav@iki.fi>> wrote:
Mon, 07 Nov 2016 19:52:09 +0300, Evgeni Burovski kirjoitti: > Note that `approx_derivative` implements several finite-difference > schemes,
In addition, I'd remind of
https://pypi.python.org/pypi/Numdifftools <https://pypi.python.org/pypi/Numdifftools>
And https://github.com/scipy/scipy/wiki/Proposal:-add-finite-difference-numerica...
<https://github.com/scipy/scipy/wiki/Proposal:-add-finite-difference-n umerical-derivatives-as-scipy.diff>
Ralf
These are tools for finite-differences of a known function. Robert (and I) are interested in finite-differences of y vs. x vectors, whether obtained from experiment or as part of a higher-level numerical method. _______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org https://mail.scipy.org/mailman/listinfo/scipy-dev