MCPcopy Index your code
hub / github.com/numpy/numpy / sinc

Function sinc

numpy/lib/_function_base_impl.py:3743–3824  ·  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)

Source from the content-addressed store, hash-verified

3741
3742@array_function_dispatch(_sinc_dispatcher)
3743def sinc(x):
3744 r"""
3745 Return the normalized sinc function.
3746
3747 The sinc function is equal to :math:`\sin(\pi x)/(\pi x)` for any argument
3748 :math:`x\ne 0`. ``sinc(0)`` takes the limit value 1, making ``sinc`` not
3749 only everywhere continuous but also infinitely differentiable.
3750
3751 .. note::
3752
3753 Note the normalization factor of ``pi`` used in the definition.
3754 This is the most commonly used definition in signal processing.
3755 Use ``sinc(x / np.pi)`` to obtain the unnormalized sinc function
3756 :math:`\sin(x)/x` that is more common in mathematics.
3757
3758 Parameters
3759 ----------
3760 x : ndarray
3761 Array (possibly multi-dimensional) of values for which to calculate
3762 ``sinc(x)``.
3763
3764 Returns
3765 -------
3766 out : ndarray
3767 ``sinc(x)``, which has the same shape as the input.
3768
3769 Notes
3770 -----
3771 The name sinc is short for "sine cardinal" or "sinus cardinalis".
3772
3773 The sinc function is used in various signal processing applications,
3774 including in anti-aliasing, in the construction of a Lanczos resampling
3775 filter, and in interpolation.
3776
3777 For bandlimited interpolation of discrete-time signals, the ideal
3778 interpolation kernel is proportional to the sinc function.
3779
3780 References
3781 ----------
3782 .. [1] Weisstein, Eric W. "Sinc Function." From MathWorld--A Wolfram Web
3783 Resource. https://mathworld.wolfram.com/SincFunction.html
3784 .. [2] Wikipedia, "Sinc function",
3785 https://en.wikipedia.org/wiki/Sinc_function
3786
3787 Examples
3788 --------
3789 >>> import numpy as np
3790 >>> import matplotlib.pyplot as plt
3791 >>> x = np.linspace(-4, 4, 41)
3792 >>> np.sinc(x)
3793 array([-3.89804309e-17, -4.92362781e-02, -8.40918587e-02, # may vary
3794 -8.90384387e-02, -5.84680802e-02, 3.89804309e-17,
3795 6.68206631e-02, 1.16434881e-01, 1.26137788e-01,
3796 8.50444803e-02, -3.89804309e-17, -1.03943254e-01,
3797 -1.89206682e-01, -2.16236208e-01, -1.55914881e-01,
3798 3.89804309e-17, 2.33872321e-01, 5.04551152e-01,
3799 7.56826729e-01, 9.35489284e-01, 1.00000000e+00,
3800 9.35489284e-01, 7.56826729e-01, 5.04551152e-01,

Callers 6

test_simpleMethod · 0.90
test_array_likeMethod · 0.90
test_bool_dtypeMethod · 0.90
test_int_dtypesMethod · 0.90
test_float_dtypesMethod · 0.90

Calls 1

whereFunction · 0.50

Tested by 6

test_simpleMethod · 0.72
test_array_likeMethod · 0.72
test_bool_dtypeMethod · 0.72
test_int_dtypesMethod · 0.72
test_float_dtypesMethod · 0.72

Used in the wild real call sites across dependent graphs

searching dependent graphs…