code: def lsf_stable(filt):
    
    lsf_data = lsf(ZFilter(filt.denpoly))
    return all(a < b for a, b in blocks(lsf_data, size=2, hop=1))
docs: Tests whether the given filter is stable or not by using the Line Spectral
    Frequencies (LSF) of the given filter. Needs NumPy.
  
    Parameters
    ----------
    filt :
      A LTI filter as a LinearFilter object.
  
    Returns
    -------
    A boolean that is true only when the LSF values from forward and backward
    prediction filters alternates. Critical stability (both forward and backward
    filters has the same LSF value) is seem as an instability, and returns
    False.
  
    See Also
    --------
    lsf :
      Gets the Line Spectral Frequencies from a filter. Needs NumPy.
    parcor_stable :
      Tests filter stability with partial correlation coefficients (reflection
      coefficients).