ref: 95ff046c698156f21e2ca0d1d8a02c23ab76969f
dir: /python/demos/demo_filterbank.py/
#! /usr/bin/env python """Create a filterbank from a list of frequencies. This demo uses `aubio.filterbank.set_triangle_bands` to build a set of triangular filters from a list of frequencies. The filterbank coefficients are then modified before being displayed.""" import aubio import numpy as np import matplotlib.pyplot as plt # sampling rate and size of the fft samplerate = 48000 win_s = 2048 # define a list of custom frequency freq_list = [60, 80, 200, 400, 800, 1600, 3200, 6400, 12800, 24000] # number of filters to create n_filters = len(freq_list) - 2 # create a new filterbank f = aubio.filterbank(n_filters, win_s) freqs = aubio.fvec(freq_list) f.set_triangle_bands(freqs, samplerate) # get the coefficients from the filterbank coeffs = f.get_coeffs() # apply a gain to fifth band coeffs[4] *= 6. # load the modified coeffs into the filterbank f.set_coeffs(coeffs) # display the band gains in a loglog plot freqs = np.vstack([np.arange(win_s // 2 + 1) * samplerate / win_s] * n_filters) plt.title('filterbank built from a list of frequencies\n' 'The 5th band has been amplified by a factor 6.') plt.loglog(freqs.T, f.get_coeffs().T, '.-') plt.xlim([50, samplerate/2]) plt.ylim([1.0e-6, 2.0e-2]) plt.xlabel('log frequency (Hz)') plt.ylabel('log amplitude') plt.show()