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Function sinc

numpy/lib/function_base.py:3633–3710  ·  view source on GitHub ↗

r""" Return the normalized sinc function. The sinc function is equal to :math:`\sin(\pi x)/(\pi x)` for any argument :math:`x\ne 0`. ``sinc(0)`` takes the limit value 1, making ``sinc`` not only everywhere continuous but also infinitely differentiable. .. note:: Note t

(x)

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3631
3632@array_function_dispatch(_sinc_dispatcher)
3633def sinc(x):
3634 r"""
3635 Return the normalized sinc function.
3636
3637 The sinc function is equal to :math:`\sin(\pi x)/(\pi x)` for any argument
3638 :math:`x\ne 0`. ``sinc(0)`` takes the limit value 1, making ``sinc`` not
3639 only everywhere continuous but also infinitely differentiable.
3640
3641 .. note::
3642
3643 Note the normalization factor of ``pi`` used in the definition.
3644 This is the most commonly used definition in signal processing.
3645 Use ``sinc(x / np.pi)`` to obtain the unnormalized sinc function
3646 :math:`\sin(x)/x` that is more common in mathematics.
3647
3648 Parameters
3649 ----------
3650 x : ndarray
3651 Array (possibly multi-dimensional) of values for which to calculate
3652 ``sinc(x)``.
3653
3654 Returns
3655 -------
3656 out : ndarray
3657 ``sinc(x)``, which has the same shape as the input.
3658
3659 Notes
3660 -----
3661 The name sinc is short for "sine cardinal" or "sinus cardinalis".
3662
3663 The sinc function is used in various signal processing applications,
3664 including in anti-aliasing, in the construction of a Lanczos resampling
3665 filter, and in interpolation.
3666
3667 For bandlimited interpolation of discrete-time signals, the ideal
3668 interpolation kernel is proportional to the sinc function.
3669
3670 References
3671 ----------
3672 .. [1] Weisstein, Eric W. "Sinc Function." From MathWorld--A Wolfram Web
3673 Resource. http://mathworld.wolfram.com/SincFunction.html
3674 .. [2] Wikipedia, "Sinc function",
3675 https://en.wikipedia.org/wiki/Sinc_function
3676
3677 Examples
3678 --------
3679 >>> import matplotlib.pyplot as plt
3680 >>> x = np.linspace(-4, 4, 41)
3681 >>> np.sinc(x)
3682 array([-3.89804309e-17, -4.92362781e-02, -8.40918587e-02, # may vary
3683 -8.90384387e-02, -5.84680802e-02, 3.89804309e-17,
3684 6.68206631e-02, 1.16434881e-01, 1.26137788e-01,
3685 8.50444803e-02, -3.89804309e-17, -1.03943254e-01,
3686 -1.89206682e-01, -2.16236208e-01, -1.55914881e-01,
3687 3.89804309e-17, 2.33872321e-01, 5.04551152e-01,
3688 7.56826729e-01, 9.35489284e-01, 1.00000000e+00,
3689 9.35489284e-01, 7.56826729e-01, 5.04551152e-01,
3690 2.33872321e-01, 3.89804309e-17, -1.55914881e-01,

Callers 2

test_simpleMethod · 0.90
test_array_likeMethod · 0.90

Calls 2

sinFunction · 0.85
whereFunction · 0.50

Tested by 2

test_simpleMethod · 0.72
test_array_likeMethod · 0.72