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#! /usr/bin/env python
import sys
from aubio import 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)
timestr = '%f' % (total_frames / float(samplerate) )
print('{:s} {:s}'.format(timestr, ' '.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()
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