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What you're missing is that the wavelet transform is a lossless conversion. If you give it $N$ points as an input, you must get $N$ points as an output. In the case of the wavelet transform, each step gives you a low-frequency result and a high-frequency result, each with $\frac{N}{2}$ points. If you keep both of them (and all your math is done with ...


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scipy's cwt is primitive and error prone; below is via ssqueezepy.cwt: Code: Note that if you seek to code the wavelet yourself, you'll need to take it to the frequency domain first (preferably analytically via Fourier transform and then sampling it, rather than via FFT), then pass it like wavelet = Wavelet(my_func); cwt(x, wavelet). import numpy as np from ...


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