Changeset a4575c4


Ignore:
Timestamp:
May 10, 2016, 6:57:43 PM (8 years ago)
Author:
Paul Brossier <piem@piem.org>
Branches:
feature/autosink, feature/cnn, feature/cnn_org, feature/constantq, feature/crepe, feature/crepe_org, feature/pitchshift, feature/pydocstrings, feature/timestretch, fix/ffmpeg5, master, pitchshift, sampler, timestretch, yinfft+
Children:
d0faeca
Parents:
01f7598
Message:

python/demos/demo_spectrogram.py: fix indent

File:
1 edited

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  • python/demos/demo_spectrogram.py

    r01f7598 ra4575c4  
    11#! /usr/bin/env python
    22
    3 import sys
     3import sys, os.path
    44from aubio import pvoc, source
    5 from numpy import array, arange, zeros, shape, log10, vstack
    6 from pylab import imshow, show, cm, axis, ylabel, xlabel, xticks, yticks
     5from numpy import array, arange, zeros, log10, vstack
     6import matplotlib.pyplot as plt
    77
    88def get_spectrogram(filename, samplerate = 0):
    9   win_s = 512                                        # fft window size
    10   hop_s = win_s / 2                                  # hop size
    11   fft_s = win_s / 2 + 1                              # spectrum bins
     9    win_s = 512                                        # fft window size
     10    hop_s = win_s / 2                                  # hop size
     11    fft_s = win_s / 2 + 1                              # spectrum bins
    1212
    13   a = source(filename, samplerate, hop_s)            # source file
    14   if samplerate == 0: samplerate = a.samplerate
    15   pv = pvoc(win_s, hop_s)                            # phase vocoder
    16   specgram = zeros([0, fft_s], dtype='float32')      # numpy array to store spectrogram
     13    a = source(filename, samplerate, hop_s)            # source file
     14    if samplerate == 0: samplerate = a.samplerate
     15    pv = pvoc(win_s, hop_s)                            # phase vocoder
     16    specgram = zeros([0, fft_s], dtype='float32')      # numpy array to store spectrogram
    1717
    18   # analysis
    19   while True:
    20     samples, read = a()                              # read file
    21     specgram = vstack((specgram,pv(samples).norm))   # store new norm vector
    22     if read < a.hop_size: break
     18    # analysis
     19    while True:
     20        samples, read = a()                              # read file
     21        specgram = vstack((specgram,pv(samples).norm))   # store new norm vector
     22        if read < a.hop_size: break
    2323
    24   # plotting
    25   imshow(log10(specgram.T + .001), origin = 'bottom', aspect = 'auto', cmap=cm.gray_r)
    26   axis([0, len(specgram), 0, len(specgram[0])])
    27   # show axes in Hz and seconds
    28   time_step = hop_s / float(samplerate)
    29   total_time = len(specgram) * time_step
    30   print "total time: %0.2fs" % total_time,
    31   print ", samplerate: %.2fkHz" % (samplerate / 1000.)
    32   n_xticks = 10
    33   n_yticks = 10
     24    # plotting
     25    fig = plt.imshow(log10(specgram.T + .001), origin = 'bottom', aspect = 'auto', cmap=plt.cm.gray_r)
     26    ax = fig.axes
     27    ax.axis([0, len(specgram), 0, len(specgram[0])])
     28    # show axes in Hz and seconds
     29    time_step = hop_s / float(samplerate)
     30    total_time = len(specgram) * time_step
     31    print "total time: %0.2fs" % total_time,
     32    print ", samplerate: %.2fkHz" % (samplerate / 1000.)
     33    n_xticks = 10
     34    n_yticks = 10
    3435
    35   def get_rounded_ticks( top_pos, step, n_ticks ):
    36       top_label = top_pos * step
    37       # get the first label
    38       ticks_first_label = top_pos * step / n_ticks
    39       # round to the closest .1
    40       ticks_first_label = round ( ticks_first_label * 10. ) / 10.
    41       # compute all labels from the first rounded one
    42       ticks_labels = [ ticks_first_label * n for n in range(n_ticks) ] + [ top_label ]
    43       # get the corresponding positions
    44       ticks_positions = [ ticks_labels[n] / step for n in range(n_ticks) ] + [ top_pos ]
    45       # convert to string
    46       ticks_labels = [  "%.1f" % x for x in ticks_labels ]
    47       # return position, label tuple to use with x/yticks
    48       return ticks_positions, ticks_labels
    49 
    50   # apply to the axis
    51   xticks( *get_rounded_ticks ( len(specgram), time_step, n_xticks ) )
    52   yticks( *get_rounded_ticks ( len(specgram[0]), (samplerate / 2. / 1000.) / len(specgram[0]), n_yticks ) )
    53   ylabel('Frequency (kHz)')
    54   xlabel('Time (s)')
     36    def get_rounded_ticks( top_pos, step, n_ticks ):
     37        top_label = top_pos * step
     38        # get the first label
     39        ticks_first_label = top_pos * step / n_ticks
     40        # round to the closest .1
     41        ticks_first_label = round ( ticks_first_label * 10. ) / 10.
     42        # compute all labels from the first rounded one
     43        ticks_labels = [ ticks_first_label * n for n in range(n_ticks) ] + [ top_label ]
     44        # get the corresponding positions
     45        ticks_positions = [ ticks_labels[n] / step for n in range(n_ticks) ] + [ top_pos ]
     46        # convert to string
     47        ticks_labels = [  "%.1f" % x for x in ticks_labels ]
     48        # return position, label tuple to use with x/yticks
     49        return ticks_positions, ticks_labels
     50 
     51    # apply to the axis
     52    x_ticks, x_labels = get_rounded_ticks ( len(specgram), time_step, n_xticks )
     53    y_ticks, y_labels = get_rounded_ticks ( len(specgram[0]), (samplerate / 1000. / 2.) / len(specgram[0]), n_yticks )
     54    ax.set_xticks( x_ticks )
     55    ax.set_yticks ( y_ticks )
     56    ax.set_xticklabels( x_labels )
     57    ax.set_yticklabels ( y_labels )
     58    ax.set_ylabel('Frequency (kHz)')
     59    ax.set_xlabel('Time (s)')
     60    ax.set_title(os.path.basename(soundfile))
     61    for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] +
     62            ax.get_xticklabels() + ax.get_yticklabels()):
     63        item.set_fontsize('x-small')
     64    return fig
    5565
    5666if __name__ == '__main__':
    57   if len(sys.argv) < 2:
    58     print "Usage: %s <filename>" % sys.argv[0]
     67    if len(sys.argv) < 2:
     68        print "Usage: %s <filename>" % sys.argv[0]
    5969  else:
    60     for soundfile in sys.argv[1:]:
    61       get_spectrogram(soundfile)
    62       # display graph
    63       show()
     70      for soundfile in sys.argv[1:]:
     71          fig = get_spectrogram(soundfile)
     72          # display graph
     73          fig.show()
     74          #outimage = os.path.basename(soundfile) + '.png'
     75          #print ("writing: " + outimage)
     76          #plt.savefig(outimage)
     77          plt.close()
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