extract_features.py 文件源码

def arspec(x, order, nfft=None, fs=1):
    """Compute the spectral density using an AR model.

    An AR model of the signal is estimated through the Yule-Walker equations;
    the estimated AR coefficient are then used to compute the spectrum, which
    can be computed explicitely for AR models.

    Parameters
    ----------
    x : array-like
        input signal
    order : int
        Order of the LPC computation.
    nfft : int
        size of the fft to compute the periodogram. If None (default), the
        length of the signal is used. if nfft > n, the signal is 0 padded.
    fs : float
        Sampling rate. By default, is 1 (normalized frequency. e.g. 0.5 is the
        Nyquist limit).

    Returns
    -------
    pxx : array-like
        The psd estimate.
    fgrid : array-like
        Frequency grid over which the periodogram was estimated.
    """

    x = np.atleast_1d(x)
    n = x.size

    if x.ndim > 1:
        raise ValueError("Only rank 1 input supported for now.")
    if not np.isrealobj(x):
        raise ValueError("Only real input supported for now.")
    if not nfft:
        nfft = n
    a, e, k = lpc(x, order)

    # This is not enough to deal correctly with even/odd size
    if nfft % 2 == 0:
        pn = nfft / 2 + 1
    else:
        pn = (nfft + 1 )/ 2

    px = 1 / np.fft.fft(a, nfft)[:pn]
    pxx = np.real(np.conj(px) * px)
    pxx /= fs / e
    fx = np.linspace(0, fs * 0.5, pxx.size)
    return pxx, fx