b7c2f6e9ccd65a53d8ae9aa0d3ee287ce9c93019,librosa/feature.py,,estimate_tuning,#,243

Before Change

    
    bins     = np.linspace(-0.5, 0.5, np.ceil(1./resolution), endpoint=False)
  
    counts, tuning = np.histogram(residual, bins)
    
    // return the histogram peak
    return tuning[np.argmax(counts)]

After Change

    // Only count magnitude where frequency is > 0
    pitch_mask = pitch > 0
    
    threshold = np.median(mag[pitch_mask])
    
    return librosa.feature.pitch_tuning( pitch[(mag > threshold) & pitch_mask], 
                                            resolution=resolution, 
                                            bins_per_octave=bins_per_octave)

Instances