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all. So, I have some time series data that I'd like to process with a wavelet transform to represent thusly. I am relatively new to the concept of wavelets. I noticed scipy.signal has a few objects, but it seems thin. Is there a library or something out there that will aid in this? Any documentation or tutorials you know of will be greatly appreciated.
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Although the discrete wavelet transform (DWT) is a powerful tool for signal and image processing, it has three serious disadvantages: shift sensitivity, poor directionality, and lack of phase information.
While the Fourier transform creates a representation of the signal in the frequency domain, the wavelet transform creates a representation of the signal in both the time and frequency domain, thereby allowing efficient access of localized information about the signal.
Have you tried PyWavelets?
import pywt
x = [3, 7, 1, 1, -2, 5, 4, 6]
# Discrete Wavelet Transform
cA, cD = pywt.dwt(x, 'db2')
x2 = pywt.idwt(cA, cD, 'db2')
There are a few examples in their documentation.
The GitHub repository has more updated information to check out as well.
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