corrected delta feature implementation

gistfile1.py

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:
      - data      : np.ndarray, shape=(d, T)
          the input data matrix (eg, spectrogram)

      - axis      : int
          the axis along which to compute deltas.
          Default is -1 (columns).

      - width     : int, odd
          Number of frames over which to compute the delta feature
          
      - order     : int
          the order of the difference operator.
          1 for first derivative, 2 for second, etc.

      - trim      : bool
          set to True to pad the output matrix to the original size.

    :returns:
      - delta_data   : np.ndarray
          delta matrix of ``data``.
    '''

    half_length     = 1 + int(np.floor(width / 2))
    window          = np.arange(half_length, -half_length - 1, -1)
    
    padding         = [(0, 0)]  * data.ndim
    padding[axis]   = (half_length, half_length)
    data            = np.pad(data, padding, mode='edge')

    delta_x = data
    
    for i in range(order):
        delta_x = scipy.signal.lfilter(window, 1, delta_x, axis=axis)
    
    if trim:
        idx = [Ellipsis] * delta_x.ndim
        idx[axis] = slice(half_length, -half_length)
        delta_x = delta_x[idx]
    
    return delta_x