source: python/demos/demo_onset_plot.py @ adc47c9

#! /usr/bin/env python

import sys
from aubio import onset, source
from numpy import array, hstack, zeros

win_s = 512                 # fft size
hop_s = win_s / 2           # 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
o = onset("default", win_s, hop_s, samplerate)

# list of onsets, in samples
onsets = []

# storage for plotted data
desc = []
tdesc = []
allsamples_max = zeros(0,)
downsample = 2  # to plot n samples / hop_s

# total number of frames read
total_frames = 0
while True:
    samples, read = s()
    is_onset = o(samples)
    if is_onset:
        this_onset = o.get_last_onset()
        print "%f" % (this_onset / float(samplerate))
        onsets.append(this_onset)
    # keep some data to plot it later
    new_maxes = (abs(samples.reshape(hop_s/downsample, downsample))).max(axis=0)
    allsamples_max = hstack([allsamples_max, new_maxes])
    desc.append(o.get_descriptor())
    tdesc.append(o.get_thresholded_descriptor())
    total_frames += read
    if read < hop_s: break

if 1:
    # do plotting
    from numpy import arange
    import matplotlib.pyplot as plt
    allsamples_max = (allsamples_max > 0) * allsamples_max
    allsamples_max_times = [ float(t) * hop_s / downsample / samplerate for t in range(len(allsamples_max)) ]
    plt1 = plt.axes([0.1, 0.75, 0.8, 0.19])
    plt2 = plt.axes([0.1, 0.1, 0.8, 0.65], sharex = plt1)
    plt.rc('lines',linewidth='.8')
    plt1.plot(allsamples_max_times,  allsamples_max, '-b')
    plt1.plot(allsamples_max_times, -allsamples_max, '-b')
    for stamp in onsets:
        stamp /= float(samplerate)
        plt1.plot([stamp, stamp], [-1., 1.], '-r')
    plt1.axis(xmin = 0., xmax = max(allsamples_max_times) )
    plt1.xaxis.set_visible(False)
    plt1.yaxis.set_visible(False)
    desc_times = [ float(t) * hop_s / samplerate for t in range(len(desc)) ]
    desc_plot = [d / max(desc) for d in desc]
    plt2.plot(desc_times, desc_plot, '-g')
    tdesc_plot = [d / max(desc) for d in tdesc]
    for stamp in onsets:
        stamp /= float(samplerate)
        plt2.plot([stamp, stamp], [min(tdesc_plot), max(desc_plot)], '-r')
    plt2.plot(desc_times, tdesc_plot, '-y')
    plt2.axis(ymin = min(tdesc_plot), ymax = max(desc_plot))
    plt.xlabel('time (s)')
    #plt.savefig('/tmp/t.png', dpi=200)
    plt.show()