Michiel de Hoon wrote:
> Hi everybody,
>
> A number of years ago I wrote a function to do Lowess smoothing to calculate
> a smooth curve through a scatter plot. I copied an example script below and
> attached the resulting figure to this mail.
> I think that such a smoothing function would be a useful addition to
> matplotlib. Does anybody have any objections against me adding this to
> matplotlib? If not, what would be a suitable place to put this function?
>
> --Michiel.
>
Michiel,
Certainly it would be good to have that function available, but I'm not
in favor of putting it in mpl. The trend has been to try to reduce
overlap among mpl, numpy, and scipy. To that end, scipy seems like the
natural home for smoothing functions.
Eric
>
> from pylab import *
>
> x = arange(0,10,0.01)
> ytrue = exp(-x/5.0) + 2*sin(x/3.0)
>
> # add random errors with a normal distribution
> y = ytrue + normal(size=len(x))
> scatter(x,y,color='cyan')
>
> # calculate a smooth curve through the scatter plot
> ys = smooth(x, y, 'lowess')
> plot(x,ys,'red',linewidth=3)
>
> # draw the true values for comparison
> plot(x,ytrue,'green',linewidth=3)
>
>
>
>
>
>
>
>
>
>
> --
>
>
>
>
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