I could not understand the principle how G is computed in find_peaks and find_peaks_adaptive , but it works good. Would you explain in more detail?

[xtj49]

In find_peaks_original, G is the mat containing maxima in different scales. In find_peaks, G needs to be mutiplied a weight. G = G * np.arange( N // 2, N // 2 - L, -1 ) # normalize to adjust for new edge regions

(1)Why it is a decreasing sequence and how to understand it？ (2)If the sum of G(in axis of 1) means the sum of maxima in different scale, would the weight be [1...L] be right which means the longest length of periodicity? (3)and would you explain the reason why find_peaks_adaptive works, it is a difficult to understand too

[xtj49]

@ig248

[xtj49]

I think if the weight was [1...L]， G can be the length covered by peaks(peaks number * scale)