Description
In the mass spectroscopy field where CWT is popular for peak identification, it has been found that applying a scale dependent weighting function to the wavelet function improves accuracy.
DOI: 10.1109/ACCESS.2022.3220640
https://doi.org/10.1080/00032719.2023.2266207
The weighting function applied in these papers is
g(a)=1/e^a
w'(t)=g(a)w(t)
where g(a) is the weighting function,
a is the scale parameter in the CWT,
w(t) is the original wavelet function,
w'(t) is the weighted wavelet function
Having an optional parameter in the pywt.cwt function for a weighting function is the request. Currently my alternative is to create a new wavelet for each scale value and run pywt.cwt in for loop. Alternatively, if including too much parameter bloat in pywt.cwt is a concern, a new function can be made separately pywt.wcwt (weighted cwt).
Thanks!