ref: 4b891e9d4fb847f19330ba31ea712c3df2bd756c
dir: /python/demos/demo_mel-energy.py/
#! /usr/bin/env python import sys from aubio import fvec, source, pvoc, filterbank from numpy import vstack, zeros win_s = 512 # fft size hop_s = win_s / 4 # hop size if len(sys.argv) < 2: print "Usage: %s <filename> [samplerate]" % sys.argv[0] sys.exit(1) filename = sys.argv[1] samplerate = 0 if len( sys.argv ) > 2: samplerate = int(sys.argv[2]) s = source(filename, samplerate, hop_s) samplerate = s.samplerate pv = pvoc(win_s, hop_s) f = filterbank(40, win_s) f.set_mel_coeffs_slaney(samplerate) energies = zeros((40,)) o = {} total_frames = 0 downsample = 2 while True: samples, read = s() fftgrain = pv(samples) new_energies = f(fftgrain) print '%f' % (total_frames / float(samplerate) ), print ' '.join(['%f' % b for b in new_energies]) energies = vstack( [energies, new_energies] ) total_frames += read if read < hop_s: break if 1: print "done computing, now plotting" import matplotlib.pyplot as plt from demo_waveform_plot import get_waveform_plot from demo_waveform_plot import set_xlabels_sample2time fig = plt.figure() plt.rc('lines',linewidth='.8') wave = plt.axes([0.1, 0.75, 0.8, 0.19]) get_waveform_plot(filename, samplerate, block_size = hop_s, ax = wave ) wave.yaxis.set_visible(False) wave.xaxis.set_visible(False) n_plots = len(energies.T) all_desc_times = [ x * hop_s for x in range(len(energies)) ] for i, band in enumerate(energies.T): ax = plt.axes ( [0.1, 0.75 - ((i+1) * 0.65 / n_plots), 0.8, 0.65 / n_plots], sharex = wave ) ax.plot(all_desc_times, band, '-', label = 'band %d' % i) #ax.set_ylabel(method, rotation = 0) ax.xaxis.set_visible(False) ax.yaxis.set_visible(False) ax.axis(xmax = all_desc_times[-1], xmin = all_desc_times[0]) ax.annotate('band %d' % i, xy=(-10, 0), xycoords='axes points', horizontalalignment='right', verticalalignment='bottom', size = 'xx-small', ) set_xlabels_sample2time( ax, all_desc_times[-1], samplerate) #plt.ylabel('spectral descriptor value') ax.xaxis.set_visible(True) plt.show()