[SciPy-User] weighted griddata
Fri Sep 17 08:47:02 CDT 2010
On 9/16/10 22:41 , firstname.lastname@example.org wrote:
>> You may need to fiddle with the smoothing parameter `s=...` for
>> > SmoothBivariateSpline.
> I was using interpolate.SmoothBivariateSpline previously and had good
> results when it worked, but I struggled with the smoothing parameter
> for so long I had to put it down. I could not figure out how to
> consistently calculate/estimate/predict a smoothing factor (from the
> data) that was not too low (and never return) or too high (and give
> blocky results).
> Is there a way to calculate an optimal smoothing factor from a data set?
I know your problem is 2-D, but for 1-D I have written the scikit
"datasmooth" that implements smoothing by regularization and includes
generalized cross validation for determining the optimal regularization
parameter (aka smoothing factor):
I know the method can be extended to 2-D, but I don't have a need or the
time to do it myself.
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