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Fonction flattop - module scipy.signal

Signature de la fonction flattop

def flattop(*args, **kwargs) 

Description

flattop.__doc__

Return a flat top window.

    .. warning:: scipy.signal.flattop is deprecated,
                 use scipy.signal.windows.flattop instead.

    Parameters
    ----------
    M : int
        Number of points in the output window. If zero or less, an empty
        array is returned.
    sym : bool, optional
        When True (default), generates a symmetric window, for use in filter
        design.
        When False, generates a periodic window, for use in spectral analysis.

    Returns
    -------
    w : ndarray
        The window, with the maximum value normalized to 1 (though the value 1
        does not appear if `M` is even and `sym` is True).

    Notes
    -----
    Flat top windows are used for taking accurate measurements of signal
    amplitude in the frequency domain, with minimal scalloping error from the
    center of a frequency bin to its edges, compared to others.  This is a
    5th-order cosine window, with the 5 terms optimized to make the main lobe
    maximally flat. [1]_

    References
    ----------
    .. [1] D'Antona, Gabriele, and A. Ferrero, "Digital Signal Processing for
           Measurement Systems", Springer Media, 2006, p. 70
           :doi:`10.1007/0-387-28666-7`.

    Examples
    --------
    Plot the window and its frequency response:

    >>> from scipy import signal
    >>> from scipy.fft import fft, fftshift
    >>> import matplotlib.pyplot as plt

    >>> window = signal.windows.flattop(51)
    >>> plt.plot(window)
    >>> plt.title("Flat top window")
    >>> plt.ylabel("Amplitude")
    >>> plt.xlabel("Sample")

    >>> plt.figure()
    >>> A = fft(window, 2048) / (len(window)/2.0)
    >>> freq = np.linspace(-0.5, 0.5, len(A))
    >>> response = 20 * np.log10(np.abs(fftshift(A / abs(A).max())))
    >>> plt.plot(freq, response)
    >>> plt.axis([-0.5, 0.5, -120, 0])
    >>> plt.title("Frequency response of the flat top window")
    >>> plt.ylabel("Normalized magnitude [dB]")
    >>> plt.xlabel("Normalized frequency [cycles per sample]")