How to smooth a curve in the right way?
Lets assume we have a dataset which might be given approximately by import numpy as np x = np.linspace(0,2*np.pi,100) y = np.sin(x) + np.random.random(100) * 0.2 Therefore we have a variation of 20% of the dataset. My first idea was to use the UnivariateSpline function of scipy, but the problem is that this does not consider the small noise in a good way. If you consider the frequencies, the background is much smaller than the signal, so a spline only of the cutoff might be an idea, but that would involve a back and forth fourier transformation, which might result in bad behaviour. Another way