nitely differentiable.

    .. note::

        Note the normalization factor of ``pi`` used in the definition.
        This is the most commonly used definition in signal processing.
        Use ``sinc(x / np.pi)`` to obtain the unnormalized sinc function
        :math:`\sin(x)/x` that is more common in mathematics.

    Parameters
    ----------
    x : ndarray
        Array (possibly multi-dimensional) of values for which to calculate
        ``sinc(x)``.

    Returns
    -------
    out : ndarray
        ``sinc(x)``, which has the same shape as the input.

    Notes
    -----
    The name sinc is short for "sine cardinal" or "sinus cardinalis".

    The sinc function is used in various signal processing applications,
    including in anti-aliasing, in the construction of a Lanczos resampling
    filter, and in interpolation.

    For bandlimited interpolation of discrete-time signals, the ideal
    interpolation kernel is proportional to the sinc function.

    References
    ----------
    .. [1] Weisstein, Eric W. "Sinc Function." From MathWorld--A Wolfram Web
           Resource. http://mathworld.wolfram.com/SincFunction.html
    .. [2] Wikipedia, "Sinc function",
           https://en.wikipedia.org/wiki/Sinc_function

    Examples
    --------
    >>> import matplotlib.pyplot as plt
    >>> x = np.linspace(-4, 4, 41)
    >>> np.sinc(x)
     array([-3.89804309e-17,  -4.92362781e-02,  -8.40918587e-02, # may vary
            -8.90384387e-02,  -5.84680802e-02,   3.89804309e-17,
            6.68206631e-02,   1.16434881e-01,   1.26137788e-01,
            8.50444803e-02,  -3.89804309e-17,  -1.03943254e-01,
            -1.89206682e-01,  -2.16236208e-01,  -1.55914881e-01,
            3.89804309e-17,   2.33872321e-01,   5.04551152e-01,
            7.56826729e-01,   9.35489284e-01,   1.00000000e+00,
            9.35489284e-01,   7.56826729e-01,   5.04551152e-01,
            2.33872321e-01,   3.89804309e-17,  -1.55914881e-01,
           -2.16236208e-01,  -1.89206682e-01,  -1.03943254e-01,
           -3.89804309e-17,   8.50444803e-02,   1.26137788e-01,
            1.16434881e-01,   6.68206631e-02,   3.89804309e-17,
            -5.84680802e-02,  -8.90384387e-02,  -8.40918587e-02,
            -4.92362781e-02,  -3.89804309e-17])

    >>> plt.plot(x, np.sinc(x))
    [<matplotlib.lines.Line2D object at 0x...>]
    >>> plt.title("Sinc Function")
    Text(0.5, 1.0, 'Sinc Function')
    >>> plt.ylabel("Amplitude")
    Text(0, 0.5, 'Amplitude')
    >>> plt.xlabel("X")
    Text(0.5, 0, 'X')
    >>> plt.show()

    r