Python's equivalent of MATLAB's cwtfilterbank

Question

I am learning signal processing and would like to know what's the python equivalent of matlab's cwtfilterbank.

I looked through pywt but did not find anything.

Some background information: I would like to process audio files with a CWT filter bank, where the wavelet filters are logarithmically spaced bandpass filters.

Many thanks in advance!

Answer 1

Avoid PyWavelets and scipy. ssqueezepy's (disclaimer, am author) scales='auto' is motivated similar to MATLAB's cwtfilterbank, and wavelets can be cached, inspected, and reused.

import numpy as np
from ssqueezepy import Wavelet, cwt
from ssqueezepy.utils import make_scales, cwt_scalebounds
from ssqueezepy.visuals import plot, imshow

# configure
signal_length = 4096
wavelet = Wavelet('morlet')

# make scales
min_scale, max_scale = cwt_scalebounds(wavelet, signal_length)
scales = make_scales(signal_length, scaletype='log', nv=8,
                     min_scale=min_scale, max_scale=max_scale)
# make filterbank
fbank = wavelet(scale=scales)

# take CWT
np.random.seed(0)
x = np.random.randn(signal_length)
Wx, _ = cwt(x, wavelet, scales=scales)

# visualize
plot(fbank.T, show=1, title="CWT filterbank")
imshow(Wx, title="|CWT(x)|", abs=1)