ref: 8122e54ad1a17377db3662878d2f5ff515d15201
dir: /python/demos/demo_specdesc.py/
#! /usr/bin/env python import sys from aubio import fvec, source, pvoc, specdesc from numpy import hstack 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] = fvec(0) o[method] = specdesc(method, win_s) total_frames = 0 downsample = 2 while True: samples, read = s() fftgrain = pv(samples) #print "%f" % ( total_frames / float(samplerate) ), for method in methods: specdesc_val = o[method](fftgrain)[0] all_descs[method] = hstack ( [all_descs[method], specdesc_val] ) #print "%f" % specdesc_val, #print 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, 10), 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()