ref: 6e157df38d1a9acb48810660b7b8f1a9e7d87a7e
dir: /python/demos/demo_specdesc.py/
#! /usr/bin/env python
import sys
import numpy as np
from aubio import source, pvoc, specdesc
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)
methods = ['default', 'energy', 'hfc', 'complex', 'phase', 'specdiff', 'kl',
'mkl', 'specflux', 'centroid', 'slope', 'rolloff', 'spread', 'skewness',
'kurtosis', 'decrease',]
all_descs = {}
o = {}
for method in methods:
cands = []
all_descs[method] = np.array([])
o[method] = specdesc(method, win_s)
total_frames = 0
downsample = 2
while True:
samples, read = s()
fftgrain = pv(samples)
#outstr = "%f" % ( total_frames / float(samplerate) )
for method in methods:
specdesc_val = o[method](fftgrain)[0]
all_descs[method] = np.append(all_descs[method], specdesc_val)
#outstr += " %f" % specdesc_val
#print(outstr)
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)
all_desc_times = [ x * hop_s for x in range(len(all_descs["default"])) ]
n_methods = len(methods)
for i, method in enumerate(methods):
#ax = fig.add_subplot (n_methods, 1, i)
#plt2 = plt.axes([0.1, 0.1, 0.8, 0.65], sharex = plt1)
ax = plt.axes ( [0.1, 0.75 - ((i+1) * 0.65 / n_methods), 0.8, 0.65 / n_methods], sharex = wave )
ax.plot(all_desc_times, all_descs[method], '-', label = method)
#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(method, xy=(-10, 0), xycoords='axes points',
horizontalalignment='right', verticalalignment='bottom',
)
set_xlabels_sample2time(ax, all_desc_times[-1], samplerate)
#plt.ylabel('spectral descriptor value')
ax.xaxis.set_visible(True)
plt.show()