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def beats_to_chords(beat_times, chord_times, chord_labels):
    '''Propagate lab-style annotations to a list of beat timings.
              
    :parameters:
      - beat_times : ndarray, shape=(m, 2)
          The time range for beat intervals.
          The `i`th beat spans time `beat_times[i, 0]` to `beat_times[i, 1]`.
          `beat_times[0, 0]` should be 0, `beat_times[-1, 1]` should be the track duration.
          
      - chord_times : ndarray, shape=(n, 2)

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def delta(data, axis=-1, width=9, order=1, trim=True):
    '''Compute delta features.

    :usage:
        >>> # Compute MFCC deltas, delta-deltas
        >>> mfccs       = librosa.feature.mfcc(y=y, sr=sr)
        >>> delta_mfcc  = librosa.feature.delta(mfccs)
        >>> delta2_mfcc = librosa.feature.delta(mfccs, order=2)

    :parameters:

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def matching(ref, est, window=0.5):
    
    n_ref, n_est = len(ref), len(est)
    
    D = np.zeros((n_ref + n_est, n_ref + n_est))
    M = (np.abs(np.subtract.outer(ref, est)) <= window).astype(int)
    
    # If we build the skew-symmetric adjacency matrix D, then rank(D) = 2 * maximum matching
    D[:n_ref, n_ref:] = M
    D[n_ref:, :n_ref] = -M.T

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