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I stumbled across some behavior I didn't expect. In the following code, I'm computing a smoothing factor automatically with normalizedsmooth=True. If I then use the resulting smooth value, keeping normalizedsmooth=True, the smoothed result is different. Any idea why?
importnumpyasnpfromcsapsimportcsapsn=25x=np.linspace(-5., 5., n)
y=np.exp(-(x/2.5)**2) + (np.random.rand(n) -0.2) *0.3xi=np.linspace(-5., 5., 150)
is_normalized=True# Smooth data and compute smoothing factor automaticallyyi_auto, smooth=csaps(x, y, xi, normalizedsmooth=is_normalized)
# Smooth data with smoothing factor 0.85yi_explicit=csaps(x, y, xi, smooth=smooth, normalizedsmooth=is_normalized)
print(np.array_equal(yi_auto, yi_explicit))
print(yi_auto[0], yi_explicit[0])
The text was updated successfully, but these errors were encountered:
Hi, thanks for this package.
I stumbled across some behavior I didn't expect. In the following code, I'm computing a smoothing factor automatically with
normalizedsmooth=True
. If I then use the resultingsmooth
value, keepingnormalizedsmooth=True
, the smoothed result is different. Any idea why?The text was updated successfully, but these errors were encountered: