1#! /usr/bin/env python 2 3import sys 4import numpy as np 5from aubio import source, pvoc, specdesc 6 7win_s = 512 # fft size 8hop_s = win_s // 4 # hop size 9 10if len(sys.argv) < 2: 11 print("Usage: %s <filename> [samplerate]" % sys.argv[0]) 12 sys.exit(1) 13 14filename = sys.argv[1] 15 16samplerate = 0 17if len( sys.argv ) > 2: samplerate = int(sys.argv[2]) 18 19s = source(filename, samplerate, hop_s) 20samplerate = s.samplerate 21 22pv = pvoc(win_s, hop_s) 23 24methods = ['default', 'energy', 'hfc', 'complex', 'phase', 'specdiff', 'kl', 25 'mkl', 'specflux', 'centroid', 'slope', 'rolloff', 'spread', 'skewness', 26 'kurtosis', 'decrease',] 27 28all_descs = {} 29o = {} 30 31for method in methods: 32 cands = [] 33 all_descs[method] = np.array([]) 34 o[method] = specdesc(method, win_s) 35 36total_frames = 0 37downsample = 2 38 39while True: 40 samples, read = s() 41 fftgrain = pv(samples) 42 #outstr = "%f" % ( total_frames / float(samplerate) ) 43 for method in methods: 44 specdesc_val = o[method](fftgrain)[0] 45 all_descs[method] = np.append(all_descs[method], specdesc_val) 46 #outstr += " %f" % specdesc_val 47 #print(outstr) 48 total_frames += read 49 if read < hop_s: break 50 51if 1: 52 print("done computing, now plotting") 53 import matplotlib.pyplot as plt 54 from demo_waveform_plot import get_waveform_plot 55 from demo_waveform_plot import set_xlabels_sample2time 56 fig = plt.figure() 57 plt.rc('lines',linewidth='.8') 58 wave = plt.axes([0.1, 0.75, 0.8, 0.19]) 59 get_waveform_plot(filename, samplerate, block_size = hop_s, ax = wave ) 60 wave.yaxis.set_visible(False) 61 wave.xaxis.set_visible(False) 62 63 all_desc_times = [ x * hop_s for x in range(len(all_descs["default"])) ] 64 n_methods = len(methods) 65 for i, method in enumerate(methods): 66 #ax = fig.add_subplot (n_methods, 1, i) 67 #plt2 = plt.axes([0.1, 0.1, 0.8, 0.65], sharex = plt1) 68 ax = plt.axes ( [0.1, 0.75 - ((i+1) * 0.65 / n_methods), 0.8, 0.65 / n_methods], sharex = wave ) 69 ax.plot(all_desc_times, all_descs[method], '-', label = method) 70 #ax.set_ylabel(method, rotation = 0) 71 ax.xaxis.set_visible(False) 72 ax.yaxis.set_visible(False) 73 ax.axis(xmax = all_desc_times[-1], xmin = all_desc_times[0]) 74 ax.annotate(method, xy=(-10, 0), xycoords='axes points', 75 horizontalalignment='right', verticalalignment='bottom', 76 ) 77 set_xlabels_sample2time(ax, all_desc_times[-1], samplerate) 78 #plt.ylabel('spectral descriptor value') 79 ax.xaxis.set_visible(True) 80 plt.show() 81