1 | #! /usr/bin/env python |
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2 | |
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3 | import sys |
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4 | from aubio import tempo, source |
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5 | |
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6 | win_s = 512 # fft size |
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7 | hop_s = win_s // 2 # hop size |
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8 | |
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9 | if len(sys.argv) < 2: |
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10 | print("Usage: %s <filename> [samplerate]" % sys.argv[0]) |
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11 | sys.exit(1) |
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12 | |
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13 | filename = sys.argv[1] |
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14 | |
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15 | samplerate = 0 |
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16 | if len( sys.argv ) > 2: samplerate = int(sys.argv[2]) |
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17 | |
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18 | s = source(filename, samplerate, hop_s) |
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19 | samplerate = s.samplerate |
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20 | o = tempo("default", win_s, hop_s, samplerate) |
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21 | |
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22 | # tempo detection delay, in samples |
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23 | # default to 4 blocks delay to catch up with |
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24 | delay = 4. * hop_s |
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25 | |
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26 | # list of beats, in samples |
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27 | beats = [] |
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28 | |
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29 | # total number of frames read |
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30 | total_frames = 0 |
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31 | while True: |
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32 | samples, read = s() |
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33 | is_beat = o(samples) |
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34 | if is_beat: |
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35 | this_beat = o.get_last_s() |
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36 | beats.append(this_beat) |
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37 | total_frames += read |
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38 | if read < hop_s: break |
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39 | |
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40 | if len(beats) > 1: |
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41 | # do plotting |
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42 | from numpy import mean, median, diff |
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43 | import matplotlib.pyplot as plt |
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44 | bpms = 60./ diff(beats) |
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45 | print('mean period: %.2fbpm, median: %.2fbpm' % (mean(bpms), median(bpms))) |
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46 | print('plotting %s' % filename) |
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47 | plt1 = plt.axes([0.1, 0.75, 0.8, 0.19]) |
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48 | plt2 = plt.axes([0.1, 0.1, 0.8, 0.65], sharex = plt1) |
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49 | plt.rc('lines',linewidth='.8') |
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50 | for stamp in beats: plt1.plot([stamp, stamp], [-1., 1.], '-r') |
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51 | plt1.axis(xmin = 0., xmax = total_frames / float(samplerate) ) |
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52 | plt1.xaxis.set_visible(False) |
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53 | plt1.yaxis.set_visible(False) |
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54 | |
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55 | # plot actual periods |
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56 | plt2.plot(beats[1:], bpms, '-', label = 'raw') |
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57 | |
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58 | # plot moving median of 5 last periods |
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59 | median_win_s = 5 |
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60 | bpms_median = [ median(bpms[i:i + median_win_s:1]) for i in range(len(bpms) - median_win_s ) ] |
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61 | plt2.plot(beats[median_win_s+1:], bpms_median, '-', label = 'median of %d' % median_win_s) |
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62 | # plot moving median of 10 last periods |
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63 | median_win_s = 20 |
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64 | bpms_median = [ median(bpms[i:i + median_win_s:1]) for i in range(len(bpms) - median_win_s ) ] |
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65 | plt2.plot(beats[median_win_s+1:], bpms_median, '-', label = 'median of %d' % median_win_s) |
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66 | |
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67 | plt2.axis(ymin = min(bpms), ymax = max(bpms)) |
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68 | #plt2.axis(ymin = 40, ymax = 240) |
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69 | plt.xlabel('time (mm:ss)') |
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70 | plt.ylabel('beats per minute (bpm)') |
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71 | plt2.set_xticklabels([ "%02d:%02d" % (t/60, t%60) for t in plt2.get_xticks()[:-1]], rotation = 50) |
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72 | |
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73 | #plt.savefig('/tmp/t.png', dpi=200) |
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74 | plt2.legend() |
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75 | plt.show() |
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76 | |
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77 | else: |
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78 | print('mean period: %.2fbpm, median: %.2fbpm' % (0, 0)) |
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79 | print('plotting %s' % filename) |
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