[SciPy-Dev] Signal Smooth

[Ralf Gommers]

On Sat, Jun 20, 2015 at 1:58 AM, Sturla Molden <sturla.molden at gmail.com>
wrote:

> Nicolas Petitclerc <npetitclerc at gmail.com> wrote:
>
> > I think it would be worth it, for the cases when you plot a 1D array, it
> > looks very messy(noisy) and you just want to quickly see the general
> trend.
> > A quick way to apply the most common methods: flat and Gaussian filters.
> A
> > few more like Savitzky-Golay, lowess would be nice, and simple to do, but
> > the idea would be to add convenience for the most basic operations.
>
> Lowess (aka loess) is a scatterplot smoother, not a signal smoother. It
> more properly belongs to the realm of statsmodels (which actually has it).
> Smoothing splines and kernel regression are other alternatives to lowess. I
> am not sure scipy.signal should implement a method to deal with unevenly
> sampled data.
>

Note that Matlab manages to put a simple moving average, loes/lowess and
Savitsky-Golay in a single function [1]. I tend to agree that this isn't
the best idea for Scipy though, and that scipy.signal shouldn't deal with
unevenly spaced data.

Ralf


[1] http://nl.mathworks.com/help/curvefit/smooth.html
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