Extract cwt

import numpy as np
import audioflux as af
from audioflux.type import SpectralFilterBankScaleType, WaveletContinueType

# Get a 880Hz's audio file path
sample_path = af.utils.sample_path('880')

# Read audio data and sample rate
audio_arr, sr = af.read(sample_path)

# Create CWT object and extract cwt
cwt_obj = af.CWT(num=84, radix2_exp=12, samplate=sr,
                 wavelet_type=WaveletContinueType.MORSE,
                 scale_type=SpectralFilterBankScaleType.OCTAVE)

# The cwt() method can only extract data of fft_length=2**radix2_exp=4096
cwt_arr = cwt_obj.cwt(audio_arr[..., :4096])
cwt_arr = np.abs(cwt_arr)

# Display spectrogram
import matplotlib.pyplot as plt
from audioflux.display import fill_spec
audio_len = audio_arr.shape[-1]
fig, ax = plt.subplots()
img = fill_spec(cwt_arr, axes=ax,
          x_coords=cwt_obj.x_coords(),
          y_coords=cwt_obj.y_coords(),
          x_axis='time', y_axis='log',
          title='CWT Spectrogram')
fig.colorbar(img, ax=ax)

In addition to CWT, you can also try BFT/ NSGT/ PWT, etc.