def METHOD_NAME(x, window=None, window_len=7):
    r"""
    Computes the periodogram
    .. math::
        I(w) = \frac{1}{n} \Big[ \sum_{t=0}^{n-1} x_t e^{itw} \Big] ^2
    at the Fourier frequencies :math:`w_j := \frac{2 \pi j}{n}`,
    :math:`j = 0, \dots, n - 1`, using the fast Fourier transform. Only the
    frequencies :math:`w_j` in :math:`[0, \pi]` and corresponding values
    :math:`I(w_j)` are returned. If a window type is given then smoothing
    is performed.
    Parameters
    ----------
    x : array_like(float)
        A flat NumPy array containing the data to smooth
    window_len : scalar(int), optional(default=7)
        An odd integer giving the length of the window.  Defaults to 7.
    window : string
        A string giving the window type. Possible values are 'flat',
        'hanning', 'hamming', 'bartlett' or 'blackman'
    Returns
    -------
    w : array_like(float)
        Fourier frequencies at which periodogram is evaluated
    I_w : array_like(float)
        Values of periodogram at the Fourier frequencies
    """
    n = len(x)
    I_w = np.abs(fft(x))**2 / n
    w = 2 * np.pi * np.arange(n) / n  # Fourier frequencies
    w, I_w = w[:int(n/2)+1], I_w[:int(n/2)+1]  # Take only values on [0, pi]
    if window:
        I_w = smooth(I_w, window_len=window_len, window=window)
    return w, I_w